Table of contents for issues of SIAM\slash ASA Journal on Uncertainty Quantification

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Volume 1, Number 1, 2013
Volume 2, Number 1, 2014
Volume 3, Number 1, 2015
Volume 4, Number 1, 2016
Volume 5, Number 1, 2017
Volume 6, Number 1, 2018
Volume 6, Number 2, 2018
Volume 6, Number 3, 2018
Volume 6, Number 4, 2018
Volume 7, Number 1, 2019
Volume 7, Number 2, 2019
Volume 7, Number 3, 2019
Volume 7, Number 4, 2019
Volume 8, Number 1, 2020
Volume 8, Number 2, 2020
Volume 8, Number 3, 2020
Volume 8, Number 4, 2020
Volume 9, Number 1, 2021
Volume 9, Number 2, 2021
Volume 9, Number 3, 2021
Volume 9, Number 4, 2021
Volume 10, Number 1, 2022
Volume 10, Number 2, 2022
Volume 10, Number 3, 2022
Volume 10, Number 4, 2022
Volume 11, Number 1, 2023
Volume 11, Number 2, 2023
Volume 11, Number 3, 2023
Volume 11, Number 4, 2023


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 1, Number 1, 2013

               James Berger and   
               Donald Estep and   
                 Max Gunzburger   Message from the Editors . . . . . . . . 1--1
          Desmond J. Higham and   
                Xuerong Mao and   
                Mikolaj Roj and   
              Qingshuo Song and   
                     George Yin   Mean Exit Times and the Multilevel Monte
                                  Carlo Method . . . . . . . . . . . . . . 2--18
                    Art B. Owen   Variance Components and Generalized
                                  Sobol' Indices . . . . . . . . . . . . . 19--41
            Jerome L. Stein and   
                     Seth Stein   Formulating Natural Hazard Policies
                                  under Uncertainty  . . . . . . . . . . . 42--56
             Victor Picheny and   
              David Ginsbourger   A Nonstationary Space-Time Gaussian
                                  Process Model for Partially Converged
                                  Simulations  . . . . . . . . . . . . . . 57--78
           Bernard Haasdonk and   
              Karsten Urban and   
               Bernhard Wieland   Reduced Basis Methods for Parameterized
                                  Partial Differential Equations with
                                  Stochastic Influences Using the
                                  Karhunen--Lo\`eve Expansion  . . . . . . 79--105
                   K. Singh and   
                   A. Sandu and   
                  M. Jardak and   
               K. W. Bowman and   
                         M. Lee   A Practical Method to Estimate
                                  Information Content in the Context of
                                  $4$D-Var Data Assimilation . . . . . . . 106--138
           Christian Bender and   
                Jessica Steiner   A Posteriori Estimates for Backward SDEs 139--163
                  T. Butler and   
                  C. Dawson and   
                      T. Wildey   Propagation of Uncertainties Using
                                  Improved Surrogate Models  . . . . . . . 164--191
            Howard C. Elman and   
                    Qifeng Liao   Reduced Basis Collocation Methods for
                                  Partial Differential Equations with
                                  Random Coefficients  . . . . . . . . . . 192--217
                   M. Arnst and   
                   C. Soize and   
                      R. Ghanem   Hybrid Sampling/Spectral Method for
                                  Solving Stochastic Coupled Problems  . . 218--243
                Loic Le Gratiet   Bayesian Analysis of Hierarchical
                                  Multifidelity Codes  . . . . . . . . . . 244--269
               Marta D'Elia and   
                 Max Gunzburger   Coarse-Grid Sampling Interpolatory
                                  Methods for Approximating Gaussian
                                  Random Fields  . . . . . . . . . . . . . 270--296
             Jan Peter Hessling   Deterministic Sampling for Propagating
                                  Model Covariance . . . . . . . . . . . . 297--318
               K. D. Jarman and   
              A. M. Tartakovsky   A Comparison of Closures for Stochastic
                                  Advection-Diffusion Equations  . . . . . 319--347
            Zackary R. Kenz and   
                H. T. Banks and   
                 Ralph C. Smith   Comparison of Frequentist and Bayesian
                                  Confidence Analysis Methods on a
                                  Viscoelastic Stenosis Model  . . . . . . 348--369
                 F. Minunno and   
               M. van Oijen and   
              D. R. Cameron and   
                  J. S. Pereira   Selecting Parameters for Bayesian
                                  Calibration of a Process-Based Model: a
                                  Methodology Based on Canonical
                                  Correlation Analysis . . . . . . . . . . 370--385
                 Qinian Jin and   
             Peter Mathé   Oracle Inequality for a Statistical
                                  Raus--Gfrerer-Type Rule  . . . . . . . . 386--407
                   Roland Pulch   Stochastic Galerkin Methods for
                                  Analyzing Equilibria of Random Dynamical
                                  Systems  . . . . . . . . . . . . . . . . 408--430
                   A. Batou and   
                       C. Soize   Calculation of Lagrange Multipliers in
                                  the Construction of Maximum Entropy
                                  Distributions in High Stochastic
                                  Dimension  . . . . . . . . . . . . . . . 431--451
                Mulin Cheng and   
              Thomas Y. Hou and   
                   Mike Yan and   
                   Zhiwen Zhang   A Data-Driven Stochastic Method for
                                  Elliptic PDEs with Random Coefficients   452--493
         Lawrence M. Murray and   
             Emlyn M. Jones and   
                   John Parslow   On Disturbance State-Space Models and
                                  the Particle Marginal
                                  Metropolis--Hastings Sampler . . . . . . 494--521
 Thordis L. Thorarinsdottir and   
           Tilmann Gneiting and   
                 Nadine Gissibl   Using Proper Divergence Functions to
                                  Evaluate Climate Models  . . . . . . . . 522--534
          Matthew J. Heaton and   
          Tamara A. Greasby and   
                Stephan R. Sain   Modeling Uncertainty in Climate Using
                                  Ensembles of Regional and Global Climate
                                  Models and Multiple Observation-Based
                                  Data Sets  . . . . . . . . . . . . . . . 535--559


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 2, Number 1, 2014

          Daniel Williamson and   
                 Adam T. Blaker   Evolving Bayesian Emulators for
                                  Structured Chaotic Time Series, with
                                  Application to Large Climate Models  . . 1--28
             Dominic Kohler and   
       Johannes Müller and   
                      Utz Wever   Cellular Probabilistic Automata --- A
                                  Novel Method for Uncertainty Propagation 29--54
                    D. P. Kouri   A Multilevel Stochastic Collocation
                                  Algorithm for Optimization of PDEs with
                                  Uncertain Coefficients . . . . . . . . . 55--81
                A. Labovsky and   
                 Max Gunzburger   An Efficient and Accurate Method for the
                                  Identification of the Most Influential
                                  Random Parameters Appearing in the Input
                                  Data for PDEs  . . . . . . . . . . . . . 82--105
                Mark Strong and   
               Jeremy E. Oakley   When Is a Model Good Enough? Deriving
                                  the Expected Value of Model Improvement
                                  via Specifying Internal Model
                                  Discrepancies  . . . . . . . . . . . . . 106--125
          Elaine T. Spiller and   
              M. J. Bayarri and   
            James O. Berger and   
            Eliza S. Calder and   
             Abani K. Patra and   
            E. Bruce Pitman and   
              Robert L. Wolpert   Automating Emulator Construction for
                                  Geophysical Hazard Maps  . . . . . . . . 126--152
                  M. Schick and   
               V. Heuveline and   
             O. P. Le Ma\^\itre   A Newton--Galerkin Method for Fluid Flow
                                  Exhibiting Uncertain Periodic Dynamics   153--173
                  T. Butler and   
                   D. Estep and   
                 S. Tavener and   
                  C. Dawson and   
                J. J. Westerink   A Measure-Theoretic Computational Method
                                  for Inverse Sensitivity Problems III:
                                  Multiple Quantities of Interest  . . . . 174--202
              Tan Bui-Thanh and   
                   Omar Ghattas   An Analysis of Infinite Dimensional
                                  Bayesian Inverse Shape Acoustic
                                  Scattering and Its Numerical
                                  Approximation  . . . . . . . . . . . . . 203--222
        Francesca Bonizzoni and   
                   Fabio Nobile   Perturbation Analysis for the Darcy
                                  Problem with Log-Normal Permeability . . 223--244
                    Art B. Owen   Sobol' Indices and Shapley Value . . . . 245--251
                    M. Grigoriu   Response Statistics for Random
                                  Heterogeneous Microstructures  . . . . . 252--275
          Joshua T. Horwood and   
                Aubrey B. Poore   Gauss von Mises Distribution for
                                  Improved Uncertainty Realism in Space
                                  Situational Awareness  . . . . . . . . . 276--304
            Laura Azzimonti and   
               Fabio Nobile and   
          Laura M. Sangalli and   
              Piercesare Secchi   Mixed Finite Elements for Spatial
                                  Regression with PDE Penalization . . . . 305--335
            Loic Le Gratiet and   
           Claire Cannamela and   
                 Bertrand Iooss   A Bayesian Approach for Global
                                  Sensitivity Analysis of (Multifidelity)
                                  Computer Codes . . . . . . . . . . . . . 336--363
                  Peng Chen and   
               Alfio Quarteroni   Weighted Reduced Basis Method for
                                  Stochastic Optimal Control Problems with
                                  Elliptic PDE Constraint  . . . . . . . . 364--396
           J. Jagalur Mohan and   
                   O. Sahni and   
                 A. Doostan and   
                   A. A. Oberai   Variational Multiscale Analysis: The
                                  Fine-Scale Green's Function for
                                  Stochastic Partial Differential
                                  Equations  . . . . . . . . . . . . . . . 397--422
                  Gary Tang and   
             Gianluca Iaccarino   Subsampled Gauss Quadrature Nodes for
                                  Estimating Polynomial Chaos Expansions   423--443
                  Xueyu Zhu and   
               Akil Narayan and   
                    Dongbin Xiu   Computational Aspects of Stochastic
                                  Collocation with Multifidelity Models    444--463
             Nikolas Kantas and   
          Alexandros Beskos and   
                     Ajay Jasra   Sequential Monte Carlo Methods for
                                  High-Dimensional Inverse Problems: a
                                  Case Study for the Navier--Stokes
                                  Equations  . . . . . . . . . . . . . . . 464--489
          David Ginsbourger and   
                Jean Baccou and   
   Clément Chevalier and   
Frédéric Perales and   
            Nicolas Garland and   
                   Yann Monerie   Bayesian Adaptive Reconstruction of
                                  Profile Optima and Optimizers  . . . . . 490--510
            Sergios Agapiou and   
      Johnathan M. Bardsley and   
    Omiros Papaspiliopoulos and   
               Andrew M. Stuart   Analysis of the Gibbs Sampler for
                                  Hierarchical Inverse Problems  . . . . . 511--544
            William Kleiber and   
            Stephan R. Sain and   
          Michael J. Wiltberger   Model Calibration via Deformation  . . . 545--563
          Robert B. Gramacy and   
                Jarad Niemi and   
                 Robin M. Weiss   Massively Parallel Approximate Gaussian
                                  Process Regression . . . . . . . . . . . 564--584
                 A. Pampell and   
               A. B. Aceves and   
                  G. Srinivasan   Predicting Dynamic Trends of the
                                  Atlantic Meridional Overturning
                                  Circulation for Transient and Stochastic
                                  Forcing Effects  . . . . . . . . . . . . 585--606
                D. O'Malley and   
               V. V. Vesselinov   A Combined Probabilistic\ldots
                                  Nonprobabilistic Decision Analysis for
                                  Contaminant Remediation  . . . . . . . . 607--621
              Andrew Gordon and   
            Catherine E. Powell   A Preconditioner for Fictitious Domain
                                  Formulations of Elliptic PDEs on
                                  Uncertain Parameterized Domains  . . . . 622--646
                   Nan Chen and   
        Dimitrios Giannakis and   
                Radu Herbei and   
                Andrew J. Majda   An MCMC Algorithm for Parameter
                                  Estimation in Signals with Hidden
                                  Intermittent Instability . . . . . . . . 647--669
                  Sharif Rahman   A Generalized ANOVA Dimensional
                                  Decomposition for Dependent Probability
                                  Measures . . . . . . . . . . . . . . . . 670--697
                 Gongjun Xu and   
                  Guang Lin and   
                   Jingchen Liu   Rare-Event Simulation for the Stochastic
                                  Korteweg--de Vries Equation  . . . . . . 698--716
             Jan Peter Hessling   Identification of Complex Models . . . . 717--744
                  G. Perrin and   
                   C. Soize and   
                 D. Duhamel and   
               C. Funfschilling   A Posteriori Error and Optimal Reduced
                                  Basis for Stochastic Processes Defined
                                  by a Finite Set of Realizations  . . . . 745--762
              Serge Gratton and   
          David Titley-Peloquin   Stochastic Conditioning of Matrix
                                  Functions  . . . . . . . . . . . . . . . 763--783
                   Feng Bao and   
                Yanzhao Cao and   
            Clayton Webster and   
                  Guannan Zhang   A Hybrid Sparse-Grid Approach for
                                  Nonlinear Filtering Problems Based on
                                  Adaptive-Domain of the Zakai Equation
                                  Approximations . . . . . . . . . . . . . 784--804
          Bertrand Gauthier and   
                   Luc Pronzato   Spectral Approximation of the IMSE
                                  Criterion for Optimal Designs in
                                  Kernel-Based Interpolation Models  . . . 805--825
           Daniel Elfverson and   
            Donald J. Estep and   
            Fredrik Hellman and   
            Axel Målqvist   Uncertainty Quantification for
                                  Approximate $p$-Quantiles for Physical
                                  Models with Stochastic Inputs  . . . . . 826--850


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 3, Number 1, 2015

           Evan Kwiatkowski and   
                     Jan Mandel   Convergence of the Square Root Ensemble
                                  Kalman Filter in the Large Ensemble
                                  Limit  . . . . . . . . . . . . . . . . . 1--17
                  Rami Atar and   
            Kenny Chowdhary and   
                    Paul Dupuis   Robust Bounds on Risk-Sensitive
                                  Functionals via Rényi Divergence  . . . . 18--33
                       C. Soize   Polynomial Chaos Expansion of a
                                  Multimodal Random Vector . . . . . . . . 34--60
    Farbod Roosta-Khorasani and   
Gábor J. Székely and   
                  Uri M. Ascher   Assessing Stochastic Algorithms for
                                  Large Scale Nonlinear Least Squares
                                  Problems Using Extremal Probabilities of
                                  Linear Combinations of Gamma Random
                                  Variables  . . . . . . . . . . . . . . . 61--90
           Sourabh Banerjee and   
         Ayanendranath Basu and   
       Sourabh Bhattacharya and   
              Smarajit Bose and   
          Dalia Chakrabarty and   
      Soumendu Sundar Mukherjee   Minimum Distance Estimation of Milky Way
                                  Model Parameters and Related Inference   91--115
            Martin Drohmann and   
                 Kevin Carlberg   The ROMES Method for Statistical
                                  Modeling of Reduced-Order-Model Error    116--145
         Matthias Hwai Yong Tan   Sequential Bayesian Polynomial Chaos
                                  Model Selection for Estimation of
                                  Sensitivity Indices  . . . . . . . . . . 146--168
                T. Arbogast and   
                   D. Estep and   
                 B. Sheehan and   
                     S. Tavener   A Posteriori Error Estimates for Mixed
                                  Finite Element and Finite Volume Methods
                                  for Parabolic Problems Coupled through a
                                  Boundary . . . . . . . . . . . . . . . . 169--198
                     J. Ray and   
                     Z. Hou and   
                   M. Huang and   
                K. Sargsyan and   
                      L. Swiler   Bayesian Calibration of the Community
                                  Land Model Using Surrogates  . . . . . . 199--233
               Giles Hooker and   
               Kevin K. Lin and   
                   Bruce Rogers   Control Theory and Experimental Design
                                  in Diffusion Processes . . . . . . . . . 234--264
               K. D. Jarman and   
              A. M. Tartakovsky   Erratum: A Comparison of Closures for
                                  Stochastic Advection-Diffusion Equations 265--266
           Michael B. Giles and   
          Tigran Nagapetyan and   
                   Klaus Ritter   Multilevel Monte Carlo Approximation of
                                  Distribution Functions and Densities . . 267--295
        Hans-Werner van Wyk and   
             Max Gunzburger and   
             John Burkhardt and   
              Miroslav Stoyanov   Power-Law Noises over General Spatial
                                  Domains and on Nonstandard Meshes  . . . 296--319
                    Si Chen and   
     Kristofer-Roy G. Reyes and   
           Maneesh K. Gupta and   
        Michael C. McAlpine and   
               Warren B. Powell   Optimal Learning in Experimental Design
                                  Using the Knowledge Gradient Policy with
                                  Application to Characterizing
                                  Nanoemulsion Stability . . . . . . . . . 320--345
       Liessman Sturlaugson and   
               John W. Sheppard   Sensitivity Analysis of Continuous Time
                                  Bayesian Network Reliability Models  . . 346--369
                  S. Golchi and   
              D. R. Bingham and   
                 H. Chipman and   
                 D. A. Campbell   Monotone Emulation of Computer
                                  Experiments  . . . . . . . . . . . . . . 370--392
            Daniel Kressner and   
               Rajesh Kumar and   
               Fabio Nobile and   
               Christine Tobler   Low-Rank Tensor Approximation for
                                  High-Order Correlation Functions of
                                  Gaussian Random Fields . . . . . . . . . 393--416
                H. T. Banks and   
            Jared Catenacci and   
                      Shuhua Hu   Asymptotic Properties of Probability
                                  Measure Estimators in a Nonparametric
                                  Model  . . . . . . . . . . . . . . . . . 417--433
             J. H. Chaudhry and   
                   D. Estep and   
                 V. Ginting and   
                     S. Tavener   A Posteriori Analysis for Iterative
                                  Solvers for Nonautonomous Evolution
                                  Problems . . . . . . . . . . . . . . . . 434--459
           Denis Belomestny and   
              Marcel Ladkau and   
              John Schoenmakers   Multilevel Simulation Based Policy
                                  Iteration for Optimal
                                  Stopping-Convergence and Complexity  . . 460--483
                Tyrus Berry and   
                    John Harlim   Nonparametric Uncertainty Quantification
                                  for Stochastic Gradient Flows  . . . . . 484--508
          Elisabeth Ullmann and   
            Catherine E. Powell   Solving Log-Transformed Random Diffusion
                                  Problems by Stochastic Galerkin Mixed
                                  Finite Element Methods . . . . . . . . . 509--534
           Sebastian J. Vollmer   Dimension-Independent MCMC Sampling for
                                  Inverse Problems with Non-Gaussian
                                  Priors . . . . . . . . . . . . . . . . . 535--561
               Asif Mahmood and   
          Robert L. Wolpert and   
                E. Bruce Pitman   A Physics-Based Emulator for the
                                  Simulation of Geophysical Mass Flows . . 562--585
                Philip B. Stark   Constraints versus Priors  . . . . . . . 586--598
                  B. Staber and   
                 J. Guilleminot   Approximate Solutions of Lagrange
                                  Multipliers for Information-Theoretic
                                  Random Field Models  . . . . . . . . . . 599--621
               Peter Benner and   
              Akwum Onwunta and   
                   Martin Stoll   Low-Rank Solution of Unsteady Diffusion
                                  Equations with Stochastic Coefficients   622--649
                 Julia Charrier   Numerical Analysis of the
                                  Advection-Diffusion of a Solute in
                                  Porous Media with Uncertainty  . . . . . 650--685
          Jeffrey C. Regier and   
                Philip B. Stark   Mini-Minimax Uncertainty Quantification
                                  for Emulators  . . . . . . . . . . . . . 686--708
         Mustafa A. Mohamad and   
         Themistoklis P. Sapsis   Probabilistic Description of Extreme
                                  Events in Intermittently Unstable
                                  Dynamical Systems Excited by Correlated
                                  Stochastic Processes . . . . . . . . . . 709--736
                Vishwas Rao and   
                   Adrian Sandu   A Posteriori Error Estimates for the
                                  Solution of Variational Inverse Problems 737--761
                Christian Kuehn   Numerical Continuation and SPDE
                                  Stability for the $2$D Cubic-Quintic
                                  Allen--Cahn Equation . . . . . . . . . . 762--789
              Xiaobing Feng and   
                Junshan Lin and   
                    Cody Lorton   An Efficient Numerical Method for
                                  Acoustic Wave Scattering in Random Media 790--822
            Oliver G. Ernst and   
         Björn Sprungk and   
       Hans-Jörg Starkloff   Analysis of the Ensemble and Polynomial
                                  Chaos Kalman Filters in Bayesian Inverse
                                  Problems . . . . . . . . . . . . . . . . 823--851
              Jonas Ballani and   
                 Lars Grasedyck   Hierarchical Tensor Approximation of
                                  Output Quantities of Parameter-Dependent
                                  PDEs . . . . . . . . . . . . . . . . . . 852--872
                    P. Wang and   
       D. A. Barajas-Solano and   
          E. Constantinescu and   
               S. Abhyankar and   
                   D. Ghosh and   
                B. F. Smith and   
                   Z. Huang and   
              A. M. Tartakovsky   Probabilistic Density Function Method
                                  for Stochastic ODEs of Power Systems
                                  with Uncertain Power Input . . . . . . . 873--896
               M. Chevreuil and   
                  R. Lebrun and   
                    A. Nouy and   
                         P. Rai   A Least-Squares Method for Sparse Low
                                  Rank Approximation of Multivariate
                                  Functions  . . . . . . . . . . . . . . . 897--921
          Elisabeth Ullmann and   
              Iason Papaioannou   Multilevel Estimation of Rare Events . . 922--953
           Michael Sinsbeck and   
          Daniel M. Tartakovsky   Impact of Data Assimilation on
                                  Cost-Accuracy Tradeoff in Multifidelity
                                  Models . . . . . . . . . . . . . . . . . 954--968
           Pierre Del Moral and   
             Lawrence M. Murray   Sequential Monte Carlo with Highly
                                  Informative Observations . . . . . . . . 969--997
            N. Hyvönen and   
                    M. Leinonen   Stochastic Galerkin Finite Element
                                  Method with Local Conductivity Basis for
                                  Electrical Impedance Tomography  . . . . 998--1019
               C. M. Bryant and   
               S. Prudhomme and   
                      T. Wildey   Error Decomposition and Adaptivity for
                                  Response Surface Approximations from
                                  PDEs with Parametric Uncertainty . . . . 1020--1045
           A. L. Teckentrup and   
                 P. Jantsch and   
              C. G. Webster and   
                  M. Gunzburger   A Multilevel Stochastic Collocation
                                  Method for Partial Differential
                                  Equations with Random Input Data . . . . 1046--1074
              T. J. Dodwell and   
                C. Ketelsen and   
                R. Scheichl and   
               A. L. Teckentrup   A Hierarchical Multilevel Markov Chain
                                  Monte Carlo Algorithm with Applications
                                  to Uncertainty Quantification in
                                  Subsurface Flow  . . . . . . . . . . . . 1075--1108
              Sergey Dolgov and   
        Boris N. Khoromskij and   
       Alexander Litvinenko and   
            Hermann G. Matthies   Polynomial Chaos Expansion of Random
                                  Coefficients and the Solution of
                                  Stochastic Partial Differential
                                  Equations in the Tensor Train Format . . 1109--1135
      Johnathan M. Bardsley and   
          Aku Seppänen and   
              Antti Solonen and   
              Heikki Haario and   
                    Jari Kaipio   Randomize-Then-Optimize for Sampling and
                                  Uncertainty Quantification in Electrical
                                  Impedance Tomography . . . . . . . . . . 1136--1158
Mihály Kovács and   
              Felix Lindner and   
       René L. Schilling   Weak Convergence of Finite Element
                                  Approximations of Linear Stochastic
                                  Evolution Equations with Additive Lévy
                                  Noise  . . . . . . . . . . . . . . . . . 1159--1199
         Daniel Sanz-Alonso and   
               Andrew M. Stuart   Long-Time Asymptotics of the Filtering
                                  Distribution for Partially Observed
                                  Chaotic Dynamical Systems  . . . . . . . 1200--1220


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 4, Number 1, 2016

              Xiaojing Wang and   
                James O. Berger   Estimating Shape Constrained Functions
                                  Using Gaussian Processes . . . . . . . . 1--25
                S. Montagna and   
                   S. T. Tokdar   Computer Emulation with Nonstationary
                                  Gaussian Processes . . . . . . . . . . . 26--47
                 Josef Dick and   
             Quoc T. Le Gia and   
               Christoph Schwab   Higher Order Quasi-Monte Carlo
                                  Integration for Holomorphic, Parametric
                                  Operator Equations . . . . . . . . . . . 48--79
                Paul Dupuis and   
      Markos A. Katsoulakis and   
            Yannis Pantazis and   
            Petr Plechác   Path-Space Information Bounds for
                                  Uncertainty Quantification and
                                  Sensitivity Analysis of Stochastic
                                  Dynamics . . . . . . . . . . . . . . . . 80--111
                  Lulu Kang and   
               V. Roshan Joseph   Kernel Approximation: From Regression to
                                  Interpolation  . . . . . . . . . . . . . 112--129
                  Sharif Rahman   The $f$-Sensitivity Index  . . . . . . . 130--162
    Bedrich Sousedík and   
                Howard C. Elman   Inverse Subspace Iteration for Spectral
                                  Stochastic Finite Element Methods  . . . 163--189
                    M. Grigoriu   Microstructure Models and Material
                                  Response by Extreme Value Theory . . . . 190--217
                  A. Mittal and   
                    X. Chen and   
                 C. H. Tong and   
                   G. Iaccarino   A Flexible Uncertainty Propagation
                                  Framework for General Multiphysics
                                  Systems  . . . . . . . . . . . . . . . . 218--243
            F. Vidal-Codina and   
               N. C. Nguyen and   
                M. B. Giles and   
                     J. Peraire   An Empirical Interpolation and
                                  Model-Variance Reduction Method for
                                  Computing Statistical Outputs of
                                  Parametrized Stochastic Partial
                                  Differential Equations . . . . . . . . . 244--265
          Mami T. Wentworth and   
             Ralph C. Smith and   
                    H. T. Banks   Parameter Selection and Verification
                                  Techniques Based on Global Sensitivity
                                  Analysis Illustrated for an HIV Model    266--297
            David Silvester and   
                        Pranjal   An Optimal Solver for Linear Systems
                                  Arising from Stochastic FEM
                                  Approximation of Diffusion Equations
                                  with Random Coefficients . . . . . . . . 298--311
           Daniel Elfverson and   
            Fredrik Hellman and   
            Axel Målqvist   A Multilevel Monte Carlo Method for
                                  Computing Failure Probabilities  . . . . 312--330
                  Jordan Ko and   
                  Henry P. Wynn   The Algebraic Method in Quadrature for
                                  Uncertainty Quantification . . . . . . . 331--357
            Achref Bachouch and   
             Emmanuel Gobet and   
                  Anis Matoussi   Empirical Regression Method for Backward
                                  Doubly Stochastic Differential Equations 358--379
                 A. Manzoni and   
                  S. Pagani and   
                     T. Lassila   Accurate Solution of Bayesian Inverse
                                  Uncertainty Quantification Problems
                                  Combining Reduced Basis Methods and
                                  Reduction Error Models . . . . . . . . . 380--412
                   Feng Bao and   
                Yanzhao Cao and   
                 Amnon Meir and   
                   Weidong Zhao   A First Order Scheme for Backward Doubly
                                  Stochastic Differential Equations  . . . 413--445
            Leonid Berlyand and   
      Pierre-Emmanuel Jabin and   
              Mykhailo Potomkin   Complexity Reduction in Many Particle
                                  Systems with Random Initial Data . . . . 446--474
    David A. Barajas-Solano and   
          Daniel M. Tartakovsky   Stochastic Collocation Methods for
                                  Nonlinear Parabolic Equations with
                                  Random Coefficients  . . . . . . . . . . 475--494
          Rachel H. Oughton and   
                 Peter S. Craig   Hierarchical Emulation: a Method for
                                  Modeling and Comparing Nested Simulators 495--519
           Helmut Harbrecht and   
             Michael Peters and   
            Markus Siebenmorgen   Multilevel Accelerated Quadrature for
                                  PDEs with Log-Normally Distributed
                                  Diffusion Coefficient  . . . . . . . . . 520--551
          Siddhartha Mishra and   
        Nils Henrik Risebro and   
           Christoph Schwab and   
              Svetlana Tokareva   Numerical Solution of Scalar
                                  Conservation Laws with Random Flux
                                  Functions  . . . . . . . . . . . . . . . 552--591
      Nawinda Chustagulprom and   
            Sebastian Reich and   
                Maria Reinhardt   A Hybrid Ensemble Transform Particle
                                  Filter for Nonlinear and Spatially
                                  Extended Dynamical Systems . . . . . . . 592--608
              H. Cagan Ozen and   
                  Guillaume Bal   Dynamical Polynomial Chaos Expansions
                                  and Long Time Evolution of Differential
                                  Equations with Random Forcing  . . . . . 609--635
                Simon Nanty and   
      Céline Helbert and   
            Amandine Marrel and   
         Nadia Pérot and   
       Clémentine Prieur   Sampling, Metamodeling, and Sensitivity
                                  Analysis of Numerical Simulators with
                                  Functional Stochastic Inputs . . . . . . 636--659
                 Sonjoy Das and   
            Sourish Chakravarty   Predictive Algorithm for Detection of
                                  Microcracks from Macroscale Observables  660--707
          Matthias De Lozzo and   
                Amandine Marrel   Estimation of the Derivative-Based
                                  Global Sensitivity Measures Using a
                                  Gaussian Process Metamodel . . . . . . . 708--738
                Joakim Beck and   
                  Serge Guillas   Sequential Design with Mutual
                                  Information for Computer Experiments
                                  (MICE): Emulation of a Tsunami Model . . 739--766
                    Rui Tuo and   
                  C. F. Jeff Wu   A Theoretical Framework for Calibration
                                  in Computer Models: Parametrization,
                                  Estimation and Convergence Properties    767--795
            Alex Gorodetsky and   
                Youssef Marzouk   Mercer Kernels and Integrated Variance
                                  Experimental Design: Connections Between
                                  Gaussian Process Regression and
                                  Polynomial Approximation . . . . . . . . 796--828
 Marcos A. Capistrán and   
  J. Andrés Christen and   
                  Sophie Donnet   Bayesian Analysis of ODEs: Solver
                                  Optimal Accuracy and Bayes Factors . . . 829--849
            Dario Azzimonti and   
                Julien Bect and   
   Clément Chevalier and   
              David Ginsbourger   Quantifying Uncertainties on Excursion
                                  Sets Under a Gaussian Random Field Prior 850--874
          Michael Frenklach and   
             Andrew Packard and   
      Gonzalo Garcia-Donato and   
                  Rui Paulo and   
                   Jerome Sacks   Comparison of Statistical and
                                  Deterministic Frameworks of Uncertainty
                                  Quantification . . . . . . . . . . . . . 875--901
           L. Mark Berliner and   
Jenný Brynjarsdóttir   A Framework for Multi-Model Ensembling   902--923
                  E. Bergou and   
                 S. Gratton and   
                  L. N. Vicente   Levenberg--Marquardt Methods Based on
                                  Probabilistic Gradient Models and
                                  Inexact Subproblem Solution, with
                                  Application to Data Assimilation . . . . 924--951
          Ulrich Römer and   
      Sebastian Schöps and   
                 Thomas Weiland   Stochastic Modeling and Regularity of
                                  the Nonlinear Elliptic curl--curl
                                  Equation . . . . . . . . . . . . . . . . 952--979
              Bruno Despres and   
                Benoit Perthame   Uncertainty Propagation; Intrusive
                                  Kinetic Formulations of Scalar
                                  Conservation Laws  . . . . . . . . . . . 980--1013
            Esperan Padonou and   
               Olivier Roustant   Polar Gaussian Processes and
                                  Experimental Designs in Circular Domains 1014--1033
              Angela Kunoth and   
               Christoph Schwab   Sparse Adaptive Tensor Galerkin
                                  Approximations of Stochastic
                                  PDE-Constrained Control Problems . . . . 1034--1059
                Eunhye Song and   
            Barry L. Nelson and   
                   Jeremy Staum   Shapley Effects for Global Sensitivity
                                  Analysis: Theory and Computation . . . . 1060--1083
                G. Malenova and   
                 M. Motamed and   
                 O. Runborg and   
                     R. Tempone   A Sparse Stochastic Collocation
                                  Technique for High-Frequency Wave
                                  Propagation with Uncertainty . . . . . . 1084--1110
                 D. Galindo and   
                 P. Jantsch and   
              C. G. Webster and   
                       G. Zhang   Accelerating Stochastic Collocation
                                  Methods for Partial Differential
                                  Equations with Random Input Data . . . . 1111--1137
                 J. Fohring and   
                       E. Haber   Adaptive $A$-Optimal Experimental Design
                                  for Linear Dynamical Systems . . . . . . 1138--1159
              Matthew Parno and   
              Tarek Moselhy and   
                Youssef Marzouk   A Multiscale Strategy for Bayesian
                                  Inference Using Transport Maps . . . . . 1160--1190
                  Colin Fox and   
              Richard A. Norton   Fast Sampling in a Linear-Gaussian
                                  Inverse Problem  . . . . . . . . . . . . 1191--1218
               Martin Eigel and   
           Christian Merdon and   
               Johannes Neumann   An Adaptive Multilevel Monte Carlo
                                  Method with Stochastic Bounds for
                                  Quantities of Interest with Uncertain
                                  Data . . . . . . . . . . . . . . . . . . 1219--1245
        Caroline Geiersbach and   
         Clemens Heitzinger and   
                 Gerhard Tulzer   Optimal Approximation of the First-Order
                                  Corrector in Multiscale Stochastic
                                  Elliptic PDE . . . . . . . . . . . . . . 1246--1262
                   Gang Bao and   
                Chuchu Chen and   
                      Peijun Li   Inverse Random Source Scattering
                                  Problems in Several Dimensions . . . . . 1263--1287
                  Ting Wang and   
               Muruhan Rathinam   Efficiency of the Girsanov
                                  Transformation Approach for Parametric
                                  Sensitivity Analysis of Stochastic
                                  Chemical Kinetics  . . . . . . . . . . . 1288--1322
         Veronica E. Bowman and   
                 David C. Woods   Emulation of Multivariate Simulators
                                  Using Thin-Plate Splines with
                                  Application to Atmospheric Dispersion    1323--1344
András László   Convergence and Error Propagation
                                  Results on a Linear Iterative Unfolding
                                  Method . . . . . . . . . . . . . . . . . 1345--1371
               Martin Eigel and   
               Christian Merdon   Local Equilibration Error Estimators for
                                  Guaranteed Error Control in Adaptive
                                  Stochastic Higher-Order Galerkin Finite
                                  Element Methods  . . . . . . . . . . . . 1372--1397
               Jiahua Jiang and   
                Yanlai Chen and   
                   Akil Narayan   A Goal-Oriented Reduced Basis
                                  Methods-Accelerated Generalized
                                  Polynomial Chaos Algorithm . . . . . . . 1398--1420


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 5, Number 1, 2017

                Peter Binev and   
               Albert Cohen and   
            Wolfgang Dahmen and   
              Ronald DeVore and   
           Guergana Petrova and   
         Przemyslaw Wojtaszczyk   Data Assimilation in Reduced Modeling    1--29
        Panagiotis Tsilifis and   
            Roger G. Ghanem and   
                   Paris Hajali   Efficient Bayesian Experimentation Using
                                  an Expected Information Gain Lower Bound 30--62
            Wim van Ackooij and   
                     R. Henrion   (Sub-)Gradient Formulae for Probability
                                  Functions of Random Inequality Systems
                                  under Gaussian Distribution  . . . . . . 63--87
            Alexandre Iolov and   
          Susanne Ditlevsen and   
           André Longtin   Optimal Design for Estimation in
                                  Diffusion Processes from First Hitting
                                  Times  . . . . . . . . . . . . . . . . . 88--110
            Michael Griebel and   
               Christian Rieger   Reproducing Kernel Hilbert Spaces for
                                  Parametric Partial Differential
                                  Equations  . . . . . . . . . . . . . . . 111--137
                 Wanting Xu and   
               Michael L. Stein   Maximum Likelihood Estimation for a
                                  Smooth Gaussian Random Field Model . . . 138--175
                       C. Soize   Optimal Partition in Terms of
                                  Independent Random Vectors of Any
                                  Non-Gaussian Vector Defined by a Set of
                                  Realizations . . . . . . . . . . . . . . 176--211
                 Ruimeng Hu and   
                 Mike Ludkovski   Sequential Design for Ranking Response
                                  Surfaces . . . . . . . . . . . . . . . . 212--239
           Timothy C. Wallstrom   On the Application of McDiarmid's
                                  Inequality to Complex Systems  . . . . . 240--245
                Hailiang Du and   
               Leonard A. Smith   Rising Above Chaotic Likelihoods . . . . 246--258
                 Dean S. Oliver   Metropolized Randomized Maximum
                                  Likelihood for Improved Sampling from
                                  Multimodal Distributions . . . . . . . . 259--277
              Rossana Vermiglio   Polynomial Chaos Expansions for the
                                  Stability Analysis of Uncertain Delay
                                  Differential Equations . . . . . . . . . 278--303
               Marc Bocquet and   
     Karthik S. Gurumoorthy and   
                  Amit Apte and   
           Alberto Carrassi and   
             Colin Grudzien and   
     Christopher K. R. T. Jones   Degenerate Kalman Filter Error
                                  Covariances and Their Convergence onto
                                  the Unstable Subspace  . . . . . . . . . 304--333
                  Dishi Liu and   
       Alexander Litvinenko and   
         Claudia Schillings and   
                  Volker Schulz   Quantification of Airfoil
                                  Geometry-Induced Aerodynamic
                                  Uncertainties --- Comparison of
                                  Approaches . . . . . . . . . . . . . . . 334--352
          Fayadhoi Ibrahima and   
              Hamdi A. Tchelepi   Multipoint Distribution of Saturation
                                  for Stochastic Nonlinear Two-Phase
                                  Transport  . . . . . . . . . . . . . . . 353--377
         M. Navarro Jimenez and   
         O. P. Le Ma\^\itre and   
                     O. M. Knio   Nonintrusive Polynomial Chaos Expansions
                                  for Sensitivity Analysis in Stochastic
                                  Differential Equations . . . . . . . . . 378--402
                 N. E. Owen and   
               P. Challenor and   
                P. P. Menon and   
                     S. Bennani   Comparison of Surrogate-Based
                                  Uncertainty Quantification Methods for
                                  Computationally Expensive Simulators . . 403--435
            Bamdad Hosseini and   
                   Nilima Nigam   Well-Posed Bayesian Inverse Problems:
                                  Priors with Exponential Tails  . . . . . 436--465
            Ahmad Ahmad Ali and   
          Elisabeth Ullmann and   
                  Michael Hinze   Multilevel Monte Carlo Analysis for
                                  Optimal Control of Elliptic PDEs with
                                  Random Coefficients  . . . . . . . . . . 466--492
                R. Scheichl and   
               A. M. Stuart and   
               A. L. Teckentrup   Quasi-Monte Carlo and Multilevel Monte
                                  Carlo Methods for Computing Posterior
                                  Expectations in Elliptic Inverse
                                  Problems . . . . . . . . . . . . . . . . 493--518
                    Chen Su and   
                      Xuemin Tu   Sequential Implicit Sampling Methods for
                                  Bayesian Inverse Problems  . . . . . . . 519--539
                 Chu V. Mai and   
                   Bruno Sudret   Surrogate Models for Oscillatory Systems
                                  Using Sparse Polynomial Chaos Expansions
                                  and Stochastic Time Warping  . . . . . . 540--571
                S. Stanhope and   
                J. E. Rubin and   
                      D. Swigon   Robustness of Solutions of the Inverse
                                  Problem for Linear Dynamical Systems
                                  with Uncertain Data  . . . . . . . . . . 572--597
                   Hao Chen and   
           Jason L. Loeppky and   
               William J. Welch   Flexible Correlation Structure for
                                  Accurate Prediction and Uncertainty
                                  Quantification in Bayesian Gaussian
                                  Process Emulation of a Computer Model    598--620
              Qingping Zhou and   
                    Zixi Hu and   
                 Zhewei Yao and   
                     Jinglai Li   A Hybrid Adaptive MCMC Algorithm in
                                  Function Spaces  . . . . . . . . . . . . 621--639
           Michael Sinsbeck and   
                 Wolfgang Nowak   Sequential Design of Computer
                                  Experiments for the Solution of Bayesian
                                  Inverse Problems . . . . . . . . . . . . 640--664
          Margaret Callahan and   
           Daniela Calvetti and   
                Erkki Somersalo   Beyond the Model Limit: Parameter
                                  Inference Across Scales  . . . . . . . . 665--693
        Ioannis Andrianakis and   
             Nicky McCreesh and   
                 Ian Vernon and   
      Trevelyan J. McKinley and   
           Jeremy E. Oakley and   
         Rebecca N. Nsubuga and   
          Michael Goldstein and   
               Richard G. White   Efficient History Matching of a High
                                  Dimensional Individual-Based HIV
                                  Transmission Model . . . . . . . . . . . 694--719
                 A. Abdulle and   
            G. A. Pavliotis and   
                        U. Vaes   Spectral Methods for Multiscale
                                  Stochastic Differential Equations  . . . 720--761
                Julien Bect and   
                    Ling Li and   
               Emmanuel Vazquez   Bayesian Subset Simulation . . . . . . . 762--786
                 Xiaoyu Liu and   
                  Serge Guillas   Dimension Reduction for Gaussian Process
                                  Emulation: an Application to the
                                  Influence of Bathymetry on Tsunami
                                  Heights  . . . . . . . . . . . . . . . . 787--812
                  Peng Chen and   
           Alfio Quarteroni and   
                Gianluigi Rozza   Reduced Basis Methods for Uncertainty
                                  Quantification . . . . . . . . . . . . . 813--869
             A. Cesmelioglu and   
                    M. Song and   
                     D. Drignei   Physics-Based Kriging Surrogates for a
                                  Class of Finite Element Codes  . . . . . 870--889
             Stefano Pagani and   
             Andrea Manzoni and   
               Alfio Quarteroni   Efficient State/Parameter Estimation in
                                  Nonlinear Unsteady PDEs by a Reduced
                                  Basis Ensemble Kalman Filter . . . . . . 890--921
                    M. Grigoriu   Estimates of System Response Maxima by
                                  Extreme Value Theory and Surrogate
                                  Models . . . . . . . . . . . . . . . . . 922--955
             Jonathan Hobbs and   
              Amy Braverman and   
               Noel Cressie and   
              Robert Granat and   
                 Michael Gunson   Simulation-Based Uncertainty
                                  Quantification for Estimating
                                  Atmospheric CO$_2$ from Satellite Data   956--985
                Art B. Owen and   
       Clémentine Prieur   On Shapley Value for Measuring
                                  Importance of Dependent Inputs . . . . . 986--1002
            Pranay Seshadri and   
               Akil Narayan and   
             Sankaran Mahadevan   Effectively Subsampled Quadratures for
                                  Least Squares Polynomial Approximations  1003--1023
                Bamdad Hosseini   Well-Posed Bayesian Inverse Problems
                                  with Infinitely Divisible and
                                  Heavy-Tailed Prior Measures  . . . . . . 1024--1060
             Noura Fajraoui and   
            Stefano Marelli and   
                   Bruno Sudret   Sequential Design of Experiment for
                                  Sparse Polynomial Chaos Expansions . . . 1061--1085
            Malek Ben Salem and   
           Olivier Roustant and   
             Fabrice Gamboa and   
                  Lionel Tomaso   Universal Prediction Distribution for
                                  Surrogate Models . . . . . . . . . . . . 1086--1109
                    M. Park and   
                M. V. Tretyakov   Stochastic Resin Transfer Molding
                                  Process  . . . . . . . . . . . . . . . . 1110--1135
                  Yulong Lu and   
              Andrew Stuart and   
                  Hendrik Weber   Gaussian Approximations for Probability
                                  Measures on $ R^d $  . . . . . . . . . . 1136--1165
          Alen Alexanderian and   
                Noemi Petra and   
              Georg Stadler and   
                   Omar Ghattas   Mean-Variance Risk-Averse Optimal
                                  Control of Systems Governed by PDEs with
                                  Random Parameter Fields Using Quadratic
                                  Approximations . . . . . . . . . . . . . 1166--1192
                     Qin Li and   
                        Li Wang   Uniform Regularity for Linear Kinetic
                                  Equations with Random Input Based on
                                  Hypocoercivity . . . . . . . . . . . . . 1193--1219
        Andrew Papanicolaou and   
      Konstantinos Spiliopoulos   Dimension Reduction in Statistical
                                  Estimation of Partially Observed
                                  Multiscale Processes . . . . . . . . . . 1220--1247
            Craig J. Newsum and   
            Catherine E. Powell   Efficient Reduced Basis Methods for
                                  Saddle Point Problems with Applications
                                  in Groundwater Flow  . . . . . . . . . . 1248--1278
              Ya-Ting Huang and   
                    James Glimm   A Novel Methodology of Stochastic Short
                                  Term Forecasting of Cloud Boundaries . . 1279--1294


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 6, Number 1, 2018

                N. Bousquet and   
                   T. Klein and   
                 V. Moutoussamy   Approximation of Limit State Surfaces in
                                  Monotonic Monte Carlo Settings, with
                                  Applications to Classification . . . . . 1--33
                Grace X. Hu and   
           David R. Kuipers and   
                      Yong Zeng   Bayesian Inference via Filtering
                                  Equations for Ultrahigh Frequency Data
                                  (I): Model and Estimation  . . . . . . . 34--60
                Grace X. Hu and   
           David R. Kuipers and   
                      Yong Zeng   Bayesian Inference via Filtering
                                  Equations for Ultrahigh Frequency Data
                                  (II): Model Selection  . . . . . . . . . 61--86
                  M. D'Elia and   
              H. C. Edwards and   
                      J. Hu and   
                  E. Phipps and   
                S. Rajamanickam   Ensemble Grouping Strategies for
                                  Embedded Stochastic Collocation Methods
                                  Applied to Anisotropic Diffusion
                                  Problems . . . . . . . . . . . . . . . . 87--117
                 Donsub Rim and   
                  Scott Moe and   
             Randall J. LeVeque   Transport Reversal for Model Reduction
                                  of Hyperbolic Partial Differential
                                  Equations  . . . . . . . . . . . . . . . 118--150
          Guillaume Damblin and   
           Pierre Barbillon and   
              Merlin Keller and   
           Alberto Pasanisi and   
             Éric Parent   Adaptive Numerical Designs for the
                                  Calibration of Computer Codes  . . . . . 151--179
    David A. Barajas-Solano and   
       Alexandre M. Tartakovsky   Probability and Cumulative Density
                                  Function Methods for the Stochastic
                                  Advection--Reaction Equation . . . . . . 180--212
         Clemens Heitzinger and   
             Gudmund Pammer and   
                  Stefan Rigger   Cubature Formulas for Multisymmetric
                                  Functions and Applications to Stochastic
                                  Partial Differential Equations . . . . . 213--242
              Alex Bespalov and   
                Leonardo Rocchi   Efficient Adaptive Algorithms for
                                  Elliptic PDEs with Random Data . . . . . 243--272
               R. Tipireddy and   
                  P. Stinis and   
              A. M. Tartakovsky   Stochastic Basis Adaptation and Spatial
                                  Domain Decomposition for Partial
                                  Differential Equations with Random
                                  Coefficients . . . . . . . . . . . . . . 273--301
                 Erkan Nane and   
                Nguyen Huy Tuan   Approximate Solutions of Inverse
                                  Problems for Nonlinear Space Fractional
                                  Diffusion Equations with Randomly
                                  Perturbed Data . . . . . . . . . . . . . 302--338
          Patrick R. Conrad and   
            Andrew D. Davis and   
         Youssef M. Marzouk and   
           Natesh S. Pillai and   
                    Aaron Smith   Parallel Local Approximation MCMC for
                                  Expensive Models . . . . . . . . . . . . 339--373
                Kookjin Lee and   
             Kevin Carlberg and   
                Howard C. Elman   Stochastic Least-Squares
                                  Petrov--Galerkin Method for
                                  Parameterized Linear Systems . . . . . . 374--396
         Emanuele Borgonovo and   
              Max D. Morris and   
                 Elmar Plischke   Functional ANOVA with Multiple
                                  Distributions: Implications for the
                                  Sensitivity Analysis of Computer
                                  Experiments  . . . . . . . . . . . . . . 397--427

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 6, Number 2, 2018

                 Arun Hegde and   
                   Wenyu Li and   
               James Oreluk and   
             Andrew Packard and   
              Michael Frenklach   Consistency Analysis for Massively
                                  Inconsistent Datasets in Bound-to-Bound
                                  Data Collaboration . . . . . . . . . . . 429--456
        Rebecca E. Morrison and   
             Todd A. Oliver and   
                Robert D. Moser   Representing Model Inadequacy: a
                                  Stochastic Operator Approach . . . . . . 457--496
           Benjamin Haaland and   
                Wenjia Wang and   
             Vaibhav Maheshwari   A Framework for Controlling Sources of
                                  Inaccuracy in Gaussian Process Emulation
                                  of Deterministic Computer Experiments    497--521
             Fabrice Gamboa and   
              Thierry Klein and   
                Agn\`es Lagnoux   Sensitivity Analysis Based on Cramér--von
                                  Mises Distance . . . . . . . . . . . . . 522--548
        Leifur Thorbergsson and   
                   Giles Hooker   Experimental Design for Partially
                                  Observed Markov Decision Processes . . . 549--567
         Andrea L. Bertozzi and   
                 Xiyang Luo and   
           Andrew M. Stuart and   
      Konstantinos C. Zygalakis   Uncertainty Quantification in
                                  Graph-Based Classification of High
                                  Dimensional Data . . . . . . . . . . . . 568--595
             Joseph Durante and   
                  Raj Patel and   
               Warren B. Powell   Scenario Generation Methods that
                                  Replicate Crossing Times in Spatially
                                  Distributed Stochastic Systems . . . . . 596--626
                      Xu He and   
                    Peter Chien   On the Instability Issue of
                                  Gradient-Enhanced Gaussian Process
                                  Emulators for Computer Experiments . . . 627--644
           Matthew D. Parno and   
             Youssef M. Marzouk   Transport Map Accelerated Markov Chain
                                  Monte Carlo  . . . . . . . . . . . . . . 645--682
                    E. Qian and   
            B. Peherstorfer and   
                D. O'Malley and   
           V. V. Vesselinov and   
                     K. Willcox   Multifidelity Monte Carlo Estimation of
                                  Variance and Sensitivity Indices . . . . 683--706
              R. N. Gantner and   
                   M. D. Peters   Higher-Order Quasi-Monte Carlo for
                                  Bayesian Shape Inversion . . . . . . . . 707--736
      Benjamin Peherstorfer and   
               Boris Kramer and   
                  Karen Willcox   Multifidelity Preconditioning of the
                                  Cross-Entropy Method for Rare Event
                                  Simulation and Failure Probability
                                  Estimation . . . . . . . . . . . . . . . 737--761
          Alexandros Beskos and   
                 Ajay Jasra and   
                   Kody Law and   
            Youssef Marzouk and   
                       Yan Zhou   Multilevel Sequential Monte Carlo with
                                  Dimension-Independent
                                  Likelihood-Informed Proposals  . . . . . 762--786
                D. P. Kouri and   
                 T. M. Surowiec   Existence and Optimality Conditions for
                                  Risk-Averse PDE-Constrained Optimization 787--815
                  Sharif Rahman   Mathematical Properties of Polynomial
                                  Dimensional Decomposition  . . . . . . . 816--844
         Jeremie Houssineau and   
               Adrian N. Bishop   Smoothing and Filtering with a Class of
                                  Outer Measures . . . . . . . . . . . . . 845--866
             Daniel Sanz-Alonso   Importance Sampling and Necessary Sample
                                  Size: an Information Theory Approach . . 867--879
               Gal Shulkind and   
                Lior Horesh and   
                     Haim Avron   Experimental Design for Nonparametric
                                  Correction of Misspecified Dynamical
                                  Models . . . . . . . . . . . . . . . . . 880--906
                   Xun Huan and   
               Cosmin Safta and   
           Khachik Sargsyan and   
            Zachary P. Vane and   
             Guilhem Lacaze and   
         Joseph C. Oefelein and   
                  Habib N. Najm   Compressive Sensing with
                                  Cross-Validation and Stop-Sampling for
                                  Sparse Polynomial Chaos Expansions . . . 907--936
              Assyr Abdulle and   
        Ibrahim Almuslimani and   
                 Gilles Vilmart   Optimal Explicit Stabilized Integrator
                                  of Weak Order 1 for Stiff and Ergodic
                                  Stochastic Differential Equations  . . . 937--964
               Peter Benner and   
                    Yue Qiu and   
                   Martin Stoll   Low-Rank Eigenvector Compression of
                                  Posterior Covariance Matrices for Linear
                                  Gaussian Inverse Problems  . . . . . . . 965--989

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 6, Number 3, 2018

    Sébastien Marmin and   
          David Ginsbourger and   
                Jean Baccou and   
               Jacques Liandrat   Warped Gaussian Processes and
                                  Derivative-Based Sequential Designs for
                                  Functions with Heterogeneous Variations  991--1018
         Clemens Heitzinger and   
     Michael Leumüller and   
             Gudmund Pammer and   
                  Stefan Rigger   Existence, Uniqueness, and a Comparison
                                  of Nonintrusive Methods for the
                                  Stochastic Nonlinear Poisson--Boltzmann
                                  Equation . . . . . . . . . . . . . . . . 1019--1042
           Gilles Blanchard and   
              Marc Hoffmann and   
              Markus Reiß   Optimal Adaptation for Early Stopping in
                                  Statistical Inverse Problems . . . . . . 1043--1075
            D. Andrew Brown and   
             Arvind Saibaba and   
         Sarah Vallélian   Low-Rank Independence Samplers in
                                  Hierarchical Bayesian Inverse Problems   1076--1100
                Peter Binev and   
               Albert Cohen and   
                  Olga Mula and   
                  James Nichols   Greedy Algorithms for Optimal
                                  Measurements Selection in State
                                  Estimation Using Reduced Models  . . . . 1101--1126
       Jehanzeb H. Chaudhry and   
            Nathanial Burch and   
                   Donald Estep   Efficient Distribution Estimation and
                                  Uncertainty Quantification for Elliptic
                                  Problems on Domains with Stochastic
                                  Boundaries . . . . . . . . . . . . . . . 1127--1150
        Ksenia N. Kyzyurova and   
            James O. Berger and   
              Robert L. Wolpert   Coupling Computer Models through Linking
                                  Their Statistical Emulators  . . . . . . 1151--1171
    Rafael Ballester-Ripoll and   
         Enrique G. Paredes and   
                Renato Pajarola   Tensor Algorithms for Advanced
                                  Sensitivity Metrics  . . . . . . . . . . 1172--1197
                   Nan Chen and   
            Andrew J. Majda and   
                    Xin T. Tong   Rigorous Analysis for Efficient
                                  Statistically Accurate Algorithms for
                                  Solving Fokker--Planck Equations in
                                  Large Dimensions . . . . . . . . . . . . 1198--1223
Andrés F. López-Lopera and   
     François Bachoc and   
           Nicolas Durrande and   
               Olivier Roustant   Finite-Dimensional Gaussian
                                  Approximation with Linear Inequality
                                  Constraints  . . . . . . . . . . . . . . 1224--1255
              S. Krumscheid and   
                      F. Nobile   Multilevel Monte Carlo Approximation of
                                  Functions  . . . . . . . . . . . . . . . 1256--1293

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 6, Number 4, 2018

           Dimitris Kamilis and   
               Nick Polydorides   Uncertainty Quantification for
                                  Low-Frequency, Time-Harmonic Maxwell
                                  Equations with Stochastic Conductivity
                                  Models . . . . . . . . . . . . . . . . . 1295--1334
             Colin Grudzien and   
           Alberto Carrassi and   
                   Marc Bocquet   Asymptotic Forecast Uncertainty and the
                                  Unstable Subspace in the Presence of
                                  Additive Model Error . . . . . . . . . . 1335--1363
           Eric Joseph Hall and   
          Markos A. Katsoulakis   Robust Information Divergences for
                                  Model-Form Uncertainty Arising from
                                  Sparse Data in Random PDE  . . . . . . . 1364--1394
    Matthias Heinkenschloss and   
               Boris Kramer and   
          Timur Takhtaganov and   
                  Karen Willcox   Conditional-Value-at-Risk Estimation via
                                  Reduced-Order Models . . . . . . . . . . 1395--1423
                 Ben Adcock and   
                   Anyi Bao and   
            John D. Jakeman and   
                   Akil Narayan   Compressed Sensing with Sparse
                                  Corruptions: Fault-Tolerant Sparse
                                  Collocation Approximations . . . . . . . 1424--1453
           Michael B. Giles and   
               Francisco Bernal   Multilevel Estimation of Expected Exit
                                  Times and Other Functionals of Stopped
                                  Diffusions . . . . . . . . . . . . . . . 1454--1474
               Davide Torlo and   
         Francesco Ballarin and   
                Gianluigi Rozza   Stabilized Weighted Reduced Basis
                                  Methods for Parametrized Advection
                                  Dominated Problems with Random Inputs    1475--1502
                 Donsub Rim and   
                 Kyle T. Mandli   Displacement Interpolation Using
                                  Monotone Rearrangement . . . . . . . . . 1503--1531
                   Xiu Yang and   
                 Weixuan Li and   
          Alexandre Tartakovsky   Sliced-Inverse-Regression--Aided Rotated
                                  Compressive Sensing Method for
                                  Uncertainty Quantification . . . . . . . 1532--1554
                Mengyang Gu and   
                      Long Wang   Scaled Gaussian Stochastic Process for
                                  Computer Model Calibration and
                                  Prediction . . . . . . . . . . . . . . . 1555--1583
                  Max D. Morris   Decomposing Functional Model Inputs for
                                  Variance-Based Sensitivity Analysis  . . 1584--1599
                  H. C. Lie and   
             T. J. Sullivan and   
               A. L. Teckentrup   Random Forward Models and
                                  Log-Likelihoods in Bayesian Inverse
                                  Problems . . . . . . . . . . . . . . . . 1600--1629
                   M. Croci and   
                M. B. Giles and   
               M. E. Rognes and   
                  P. E. Farrell   Efficient White Noise Sampling and
                                  Coupling for Multilevel Monte Carlo with
                                  Nonnested Meshes . . . . . . . . . . . . 1630--1655
             Ana Djurdjevac and   
         Charles M. Elliott and   
             Ralf Kornhuber and   
                  Thomas Ranner   Evolving Surface Finite Element Methods
                                  for Random Advection--Diffusion
                                  Equations  . . . . . . . . . . . . . . . 1656--1684
            Arindam Fadikar and   
                Dave Higdon and   
             Jiangzhuo Chen and   
                Bryan Lewis and   
   Srinivasan Venkatramanan and   
                 Madhav Marathe   Calibrating a Stochastic, Agent-Based
                                  Model Using Quantile-Based Emulation . . 1685--1706
               Andrea Barth and   
                  Andreas Stein   A Study of Elliptic Partial Differential
                                  Equations with Jump Diffusion
                                  Coefficients . . . . . . . . . . . . . . 1707--1743
                Kookjin Lee and   
        Bedrich Sousedík   Inexact Methods for Symmetric Stochastic
                                  Eigenvalue Problems  . . . . . . . . . . 1744--1776


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 7, Number 1, 2019

Frédéric Cérou and   
             Bernard Delyon and   
             Arnaud Guyader and   
                Mathias Rousset   On the Asymptotic Normality of Adaptive
                                  Multilevel Splitting . . . . . . . . . . 1--30
                 Wanting Xu and   
           Michael L. Stein and   
                     Ian Wisher   Modeling and Predicting Chaotic Circuit
                                  Data . . . . . . . . . . . . . . . . . . 31--52
                 Minyong R. Lee   Modified Active Subspaces Using the
                                  Average of Gradients . . . . . . . . . . 53--66
             Joseph L. Hart and   
               Julie Bessac and   
         Emil M. Constantinescu   Global Sensitivity Analysis for
                                  Statistical Model Parameters . . . . . . 67--92
         Gianluca Detommaso and   
                Tim Dodwell and   
                   Rob Scheichl   Continuous Level Monte Carlo and
                                  Sample-Adaptive Model Hierarchies  . . . 93--116
           Kayla D. Coleman and   
              Allison Lewis and   
             Ralph C. Smith and   
             Brian Williams and   
                 Max Morris and   
               Bassam Khuwaileh   Gradient-Free Construction of Active
                                  Subspaces for Dimension Reduction in
                                  Complex Models with Applications to
                                  Neutronics . . . . . . . . . . . . . . . 117--142
           Toshihiro Yamada and   
                 Kenta Yamamoto   Second Order Discretization of
                                  Bismut--Elworthy--Li Formula:
                                  Application to Sensitivity Analysis  . . 143--173
          Andreas Van Barel and   
              Stefan Vandewalle   Robust Optimization of PDEs with Random
                                  Coefficients Using a Multilevel Monte
                                  Carlo Method . . . . . . . . . . . . . . 174--202
            Daniel J. Perry and   
            Robert M. Kirby and   
               Akil Narayan and   
               Ross T. Whitaker   Allocation Strategies for High Fidelity
                                  Models in the Multifidelity Regime . . . 203--231
        Zachary del Rosario and   
                Minyong Lee and   
             Gianluca Iaccarino   Lurking Variable Detection via
                                  Dimensional Analysis . . . . . . . . . . 232--259
              Sergey Dolgov and   
                Robert Scheichl   A Hybrid Alternating Least
                                  Squares--TT-Cross Algorithm for
                                  Parametric PDEs  . . . . . . . . . . . . 260--291
           Constantin Grigo and   
 Phaedon-Stelios Koutsourelakis   Bayesian Model and Dimension Reduction
                                  for Uncertainty Propagation:
                                  Applications in Random Media . . . . . . 292--323
             N. Nüsken and   
                G. A. Pavliotis   Constructing Sampling Schemes via
                                  Coupling: Markov Semigroups and Optimal
                                  Transport  . . . . . . . . . . . . . . . 324--382

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 7, Number 2, 2019

               Andreas Adelmann   On Nonintrusive Uncertainty
                                  Quantification and Surrogate Model
                                  Construction in Particle Accelerator
                                  Modeling . . . . . . . . . . . . . . . . 383--416
             Adrien Spagnol and   
          Rodolphe Le Riche and   
     Sébastien Da Veigao   Global Sensitivity Analysis for
                                  Optimization with Variable Selection . . 417--443
               Colin Cotter and   
               Simon Cotter and   
                   Paul Russell   Ensemble Transport Adaptive Importance
                                  Sampling . . . . . . . . . . . . . . . . 444--471
          Rodrigo Iza-Teran and   
                  Jochen Garcke   A Geometrical Method for Low-Dimensional
                                  Representations of Simulations . . . . . 472--496
           Michael B. Giles and   
          Abdul-Lateef Haji-Ali   Multilevel Nested Simulation for
                                  Efficient Risk Estimation  . . . . . . . 497--525
            Christian Kahle and   
               Kei Fong Lam and   
                 Jonas Latz and   
              Elisabeth Ullmann   Bayesian Parameter Identification in
                                  Cahn--Hilliard Models for Biological
                                  Growth . . . . . . . . . . . . . . . . . 526--552
                        Rui Tuo   Adjustments to Computer Models via
                                  Projected Kernel Calibration . . . . . . 553--578
          Benjamin Peherstorfer   Multifidelity Monte Carlo Estimation
                                  with Adaptive Low-Fidelity Models  . . . 579--603
                Dave Osthus and   
       Scott A. Vander Wiel and   
          Nelson M. Hoffman and   
           Frederick J. Wysocki   Prediction Uncertainties beyond the
                                  Range of Experience: a Case Study in
                                  Inertial Confinement Fusion Implosion
                                  Experiments  . . . . . . . . . . . . . . 604--633
               Roland Pulch and   
               Florian Augustin   Stability Preservation in Stochastic
                                  Galerkin Projections of Dynamical
                                  Systems  . . . . . . . . . . . . . . . . 634--651
           Christian Clason and   
                Tapio Helin and   
           Remo Kretschmann and   
              Petteri Piiroinen   Generalized Modes in Bayesian Inverse
                                  Problems . . . . . . . . . . . . . . . . 652--684
                 David Aristoff   Generalizing Parallel Replica Dynamics:
                                  Trajectory Fragments, Asynchronous
                                  Computing, and PDMPs . . . . . . . . . . 685--719
                 Furong Sun and   
          Robert B. Gramacy and   
           Benjamin Haaland and   
              Earl Lawrence and   
                  Andrew Walker   Emulating Satellite Drag from Large
                                  Simulation Experiments . . . . . . . . . 720--759
               Nathalie Ayi and   
                     Erwan Faou   Analysis of an Asymptotic Preserving
                                  Scheme for Stochastic Linear Kinetic
                                  Equations in the Diffusion Limit . . . . 760--785

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 7, Number 3, 2019

    Christopher Müller and   
          Sebastian Ullmann and   
                      Jens Lang   A Bramble--Pasciak Conjugate Gradient
                                  Method for Discrete Stokes Equations
                                  with Random Viscosity  . . . . . . . . . 787--805
             James M. Scott and   
               M. Paul Laiu and   
                  Cory D. Hauck   Analysis of the Zero Relaxation Limit of
                                  Hyperbolic Balance Laws with Random
                                  Initial Data . . . . . . . . . . . . . . 806--837
                 Ian Vernon and   
          Samuel E. Jackson and   
            Jonathan A. Cumming   Known Boundary Emulation of Complex
                                  Computer Models  . . . . . . . . . . . . 838--876
            Matthew J. Zahr and   
          Kevin T. Carlberg and   
                  Drew P. Kouri   An Efficient, Globally Convergent Method
                                  for Optimization Under Uncertainty Using
                                  Adaptive Model Reduction and Sparse
                                  Grids  . . . . . . . . . . . . . . . . . 877--912
             Lukas Herrmann and   
           Christoph Schwab and   
                     Jakob Zech   Uncertainty Quantification for Spectral
                                  Fractional Diffusion: Sparsity Analysis
                                  of Parametric Solutions  . . . . . . . . 913--947
              U. Khristenko and   
              L. Scarabosio and   
            P. Swierczynski and   
                 E. Ullmann and   
                    B. Wohlmuth   Analysis of Boundary Effects on
                                  PDE-Based Sampling of Whittle--Matérn
                                  Random Fields  . . . . . . . . . . . . . 948--974
               David Swigon and   
         Shelby R. Stanhope and   
                Sven Zenker and   
              Jonathan E. Rubin   On the Importance of the Jacobian
                                  Determinant in Parameter Inference for
                                  Random Parameter and Random Measurement
                                  Error Models . . . . . . . . . . . . . . 975--1006
         Agnimitra Dasgupta and   
                   Debraj Ghosh   Failure Probability Estimation of Linear
                                  Time Varying Systems by Progressive
                                  Refinement of Reduced Order Models . . . 1007--1028
         Giovanni Dematteis and   
              Tobias Grafke and   
            Eric Vanden-Eijnden   Extreme Event Quantification in
                                  Dynamical Systems with Random Components 1029--1059
           Giovanni Rabitti and   
             Emanuele Borgonovo   A Shapley--Owen Index for Interaction
                                  Quantification . . . . . . . . . . . . . 1060--1075
               Mohammad Motamed   Fuzzy-Stochastic Partial Differential
                                  Equations  . . . . . . . . . . . . . . . 1076--1104
          Arvind K. Saibaba and   
         Johnathan Bardsley and   
            D. Andrew Brown and   
              Alen Alexanderian   Efficient Marginalization-Based MCMC
                                  Methods for Hierarchical Bayesian
                                  Inverse Problems . . . . . . . . . . . . 1105--1131

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 7, Number 4, 2019

             Matthias H. Y. Tan   Gaussian Process Modeling of Finite
                                  Element Models with Functional Inputs    1133--1161
              M. Gunzburger and   
                 T. Iliescu and   
            M. Mohebujjaman and   
                    M. Schneier   An Evolve-Filter-Relax Stabilized
                                  Reduced Order Stochastic Collocation
                                  Method for the Time-Dependent
                                  Navier--Stokes Equations . . . . . . . . 1162--1184
                Bamdad Hosseini   Two Metropolis--Hastings Algorithms for
                                  Posterior Measures with Non-Gaussian
                                  Priors in Infinite Dimensions  . . . . . 1185--1223
             Joseph L. Hart and   
              Pierre A. Gremaud   Robustness of the Sobol' Indices to
                                  Marginal Distribution Uncertainty  . . . 1224--1244
                   Ru Zhang and   
               C. Devon Lin and   
                  Pritam Ranjan   A Sequential Design Approach for
                                  Calibrating Dynamic Computer Simulators  1245--1274
                Kookjin Lee and   
            Howard C. Elman and   
        Bedrich Sousedík   A Low-Rank Solver for the Navier--Stokes
                                  Equations with Uncertain Viscosity . . . 1275--1300
            Pranay Seshadri and   
               Shaowu Yuchi and   
              Geoffrey T. Parks   Dimension Reduction via Gaussian Ridge
                                  Functions  . . . . . . . . . . . . . . . 1301--1322
                 Paul Mycek and   
              Matthias De Lozzo   Multilevel Monte Carlo Covariance
                                  Estimation for the Computation of Sobol'
                                  Indices  . . . . . . . . . . . . . . . . 1323--1348
          Jaroslav Vondrejc and   
            Hermann G. Matthies   Accurate Computation of Conditional
                                  Expectation for Highly Nonlinear
                                  Problems . . . . . . . . . . . . . . . . 1349--1368
            Malek Ben Salem and   
     François Bachoc and   
           Olivier Roustant and   
             Fabrice Gamboa and   
                  Lionel Tomaso   Gaussian Process-Based Dimension
                                  Reduction for Goal-Oriented Sequential
                                  Design . . . . . . . . . . . . . . . . . 1369--1397
              T. J. Dodwell and   
                C. Ketelsen and   
                R. Scheichl and   
               A. L. Teckentrup   ERRATUM: A Hierarchical Multilevel
                                  Markov Chain Monte Carlo Algorithm with
                                  Applications to Uncertainty
                                  Quantification in Subsurface Flow  . . . 1398--1399


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 8, Number 1, 2020

          Victoria Volodina and   
              Daniel Williamson   Diagnostics-Driven Nonstationary
                                  Emulators Using Kernel Mixtures  . . . . 1--26
                  Sharif Rahman   A Spline Chaos Expansion . . . . . . . . 27--57
              O. R. Pembery and   
                   E. A. Spence   The Helmholtz Equation in Random Media:
                                  Well-Posedness and A Priori Bounds . . . 58--87
Marie Kubínová and   
         Ivana Pultarová   Block Preconditioning of Stochastic
                                  Galerkin Problems: New Two-sided
                                  Guaranteed Spectral Bounds . . . . . . . 88--113
         Thomas P. Prescott and   
                  Ruth E. Baker   Multifidelity Approximate Bayesian
                                  Computation  . . . . . . . . . . . . . . 114--138
        Laurent van den Bos and   
          Benjamin Sanderse and   
              Wim Bierbooms and   
              Gerard van Bussel   Generating Nested Quadrature Rules with
                                  Positive Weights based on Arbitrary
                                  Sample Sets  . . . . . . . . . . . . . . 139--169
     Emil M. Constantinescu and   
         Noémi Petra and   
               Julie Bessac and   
                Cosmin G. Petra   Statistical Treatment of Inverse
                                  Problems Constrained by Differential
                                  Equations-Based Models with Stochastic
                                  Terms  . . . . . . . . . . . . . . . . . 170--197
            Anthony Fillion and   
               Marc Bocquet and   
              Serge Gratton and   
          Selime Gürol and   
                    Pavel Sakov   An Iterative Ensemble Kalman Smoother in
                                  Presence of Additive Model Error . . . . 198--228
      Konstantinos Spiliopoulos   Information Geometry for Approximate
                                  Bayesian Computation . . . . . . . . . . 229--260
              Adi Ditkowski and   
                Gadi Fibich and   
                     Amir Sagiv   Density Estimation in Uncertainty
                                  Propagation Problems Using a Surrogate
                                  Model  . . . . . . . . . . . . . . . . . 261--300
               Ruben Aylwin and   
       Carlos Jerez-Hanckes and   
           Christoph Schwab and   
                     Jakob Zech   Domain Uncertainty Quantification in
                                  Computational Electromagnetics . . . . . 301--341
            Matteo Giordano and   
                 Hanne Kekkonen   Bernstein--von Mises Theorems and
                                  Uncertainty Quantification for Linear
                                  Inverse Problems . . . . . . . . . . . . 342--373
              Richard Nickl and   
           Sara van de Geer and   
                      Sven Wang   Convergence Rates for Penalized Least
                                  Squares Estimators in PDE Constrained
                                  Regression Problems  . . . . . . . . . . 374--413
              Assyr Abdulle and   
               Andrea Di Blasio   A Bayesian Numerical Homogenization
                                  Method for Elliptic Multiscale Inverse
                                  Problems . . . . . . . . . . . . . . . . 414--450
                     Jonas Latz   On the Well-posedness of Bayesian
                                  Inverse Problems . . . . . . . . . . . . 451--482
                 Dan Crisan and   
  Alberto López-Yela and   
                 Joaquin Miguez   Stable Approximation Schemes for Optimal
                                  Filters  . . . . . . . . . . . . . . . . 483--509

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 8, Number 2, 2020

                 P. Héas   Selecting Reduced Models in the
                                  Cross-Entropy Method . . . . . . . . . . 511--538
           Jeremiah Birrell and   
                 Luc Rey-Bellet   Uncertainty Quantification for Markov
                                  Processes via Variational Principles and
                                  Functional Inequalities  . . . . . . . . 539--572
                Dave Osthus and   
           Jeffrey D. Hyman and   
               Satish Karra and   
              Nishant Panda and   
               Gowri Srinivasan   A Probabilistic Clustering Approach for
                                  Identifying Primary Subnetworks of
                                  Discrete Fracture Networks with
                                  Quantified Uncertainty . . . . . . . . . 573--600
             Daniel Schaden and   
              Elisabeth Ullmann   On Multilevel Best Linear Unbiased
                                  Estimators . . . . . . . . . . . . . . . 601--635
                    Kui Ren and   
         Sarah Vallélian   Characterizing Impacts of Model
                                  Uncertainties in Quantitative
                                  Photoacoustics . . . . . . . . . . . . . 636--667
    Matthias Heinkenschloss and   
               Boris Kramer and   
              Timur Takhtaganov   Adaptive Reduced-Order Model
                                  Construction for Conditional
                                  Value-at-Risk Estimation . . . . . . . . 668--692
             Baptiste Broto and   
     François Bachoc and   
                Marine Depecker   Variance Reduction for Estimation of
                                  Shapley Effects and Adaptation to
                                  Unknown Input Distribution . . . . . . . 693--716
             Ying-Chao Hung and   
         George Michailidis and   
              Horace PakHai Lok   Locating Infinite Discontinuities in
                                  Computer Experiments . . . . . . . . . . 717--747
          Jürgen Dölz   A Higher Order Perturbation Approach for
                                  Electromagnetic Scattering Problems on
                                  Random Domains . . . . . . . . . . . . . 748--774
           Olivier Roustant and   
     Espéran Padonou and   
               Yves Deville and   
    Alo\"\is Clément and   
           Guillaume Perrin and   
                Jean Giorla and   
                     Henry Wynn   Group Kernels for Gaussian Process
                                  Metamodels with Categorical Inputs . . . 775--806
           Gerardo Severino and   
                Salvatore Cuomo   Uncertainty Quantification of Unsteady
                                  Flows Generated by Line-Sources Through
                                  Heterogeneous Geological Formations  . . 807--825

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 8, Number 3, 2020

            Arpan Mukherjee and   
                  Rahul Rai and   
              Puneet Singla and   
             Tarunraj Singh and   
                    Abani Patra   Overlapping Clustering Based Technique
                                  for Scalable Uncertainty Quantification
                                  in Physical Systems  . . . . . . . . . . 827--859
             Kevin Bulthuis and   
               Frank Pattyn and   
                  Maarten Arnst   A Multifidelity Quantile-Based Approach
                                  for Confidence Sets of Random Excursion
                                  Sets with Application to Ice-Sheet
                                  Dynamics . . . . . . . . . . . . . . . . 860--890
             Matthias H. Y. Tan   Bayesian Optimization of Expected
                                  Quadratic Loss for Multiresponse
                                  Computer Experiments with Internal Noise 891--925
              Toni Karvonen and   
               George Wynne and   
              Filip Tronarp and   
                Chris Oates and   
          Simo Särkkä   Maximum Likelihood Estimation and
                                  Uncertainty Quantification for Gaussian
                                  Process Approximation of Deterministic
                                  Functions  . . . . . . . . . . . . . . . 926--958
               Luc Pronzato and   
            Anatoly Zhigljavsky   Bayesian Quadrature, Energy
                                  Minimization, and Space-Filling Design   959--1011
   Caroline Moosmüller and   
             Felix Dietrich and   
          Ioannis G. Kevrekidis   A Geometric Approach to the Transport of
                                  Discontinuous Densities  . . . . . . . . 1012--1035
             Jeff Borggaard and   
         Nathan Glatt-Holtz and   
                Justin Krometis   A Bayesian Approach to Estimating
                                  Background Flows from a Passive Scalar   1036--1060
           S. Crépey and   
                    G. Fort and   
                   E. Gobet and   
                  U. Stazhynski   Uncertainty Quantification for
                                  Stochastic Approximation Limits Using
                                  Chaos Expansion  . . . . . . . . . . . . 1061--1089
       Amirhossein Taghvaei and   
          Prashant G. Mehta and   
                   Sean P. Meyn   Diffusion Map-based Algorithm for Gain
                                  Function Approximation in the Feedback
                                  Particle Filter  . . . . . . . . . . . . 1090--1117
                   Lun Yang and   
                  Peng Wang and   
          Daniel M. Tartakovsky   Resource-Constrained Model Selection for
                                  Uncertainty Propagation and Data
                                  Assimilation . . . . . . . . . . . . . . 1118--1138
            Aaron R. Dinner and   
             Erik H. Thiede and   
            Brian Van Koten and   
                 Jonathan Weare   Stratification as a General Variance
                                  Reduction Method for Markov Chain Monte
                                  Carlo  . . . . . . . . . . . . . . . . . 1139--1188
               Martin Eigel and   
           Manuel Marschall and   
               Michael Multerer   An Adaptive Stochastic Galerkin Tensor
                                  Train Discretization for Randomly
                                  Perturbed Domains  . . . . . . . . . . . 1189--1214
                 Linjie Wen and   
                 Jiangqi Wu and   
                  Linjun Lu and   
                     Jinglai Li   A Defensive Marginal Particle Filtering
                                  Method for Data Assimilation . . . . . . 1215--1235
          Tomohiko Hironaka and   
           Michael B. Giles and   
               Takashi Goda and   
                    Howard Thom   Multilevel Monte Carlo Estimation of the
                                  Expected Value of Sample Information . . 1236--1259

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 8, Number 4, 2020

              Marc Mignolet and   
                Christian Soize   Compressed Principal Component Analysis
                                  of Non-Gaussian Vectors  . . . . . . . . 1261--1286
              Kellin Rumsey and   
             Gabriel Huerta and   
               Justin Brown and   
                    Lauren Hund   Dealing with Measurement Uncertainties
                                  as Nuisance Parameters in Bayesian Model
                                  Calibration  . . . . . . . . . . . . . . 1287--1309
           Aretha L. Teckentrup   Convergence of Gaussian Process
                                  Regression with Estimated
                                  Hyper-Parameters and Applications in
                                  Bayesian Inverse Problems  . . . . . . . 1310--1337
                    Yang Yu and   
                 Ning Zhang and   
            Daniel W. Apley and   
                   Wenxin Jiang   Including a Nugget Effect in Lifted
                                  Brownian Covariance Models . . . . . . . 1338--1357
                      Pulong Ma   Objective Bayesian Analysis of a
                                  Cokriging Model for Hierarchical
                                  Multifidelity Codes  . . . . . . . . . . 1358--1382
            Simon L. Cotter and   
      Ioannis G. Kevrekidis and   
                Paul T. Russell   Transport Map Accelerated Adaptive
                                  Importance Sampling, and Application to
                                  Inverse Problems Arising from Multiscale
                                  Stochastic Reaction Networks . . . . . . 1383--1413
                John Harlim and   
         Daniel Sanz-Alonso and   
                     Ruiyi Yang   Kernel Methods for Bayesian Elliptic
                                  Inverse Problems on Manifolds  . . . . . 1414--1445
               Colin Cotter and   
                 Dan Crisan and   
             Darryl D. Holm and   
                    Wei Pan and   
                Igor Shevchenko   A Particle Filter for Stochastic
                                  Advection by Lie Transport: a Case Study
                                  for the Damped and Forced Incompressible
                                  Two-Dimensional Euler Equation . . . . . 1446--1492
                     Qin Li and   
               Jian-Guo Liu and   
                     Ruiwen Shu   Sensitivity Analysis of Burgers'
                                  Equation with Shocks . . . . . . . . . . 1493--1521
                    Rui Tuo and   
                   Yan Wang and   
                  C. F. Jeff Wu   On the Improved Rates of Convergence for
                                  Matérn-Type Kernel Ridge Regression with
                                  Application to Calibration of Computer
                                  Models . . . . . . . . . . . . . . . . . 1522--1547
                       Nan Chen   An Information Criterion for Choosing
                                  Observation Locations in Data
                                  Assimilation and Prediction  . . . . . . 1548--1573


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 9, Number 1, 2021

                   Shuai Lu and   
               Pingping Niu and   
                   Frank Werner   On the Asymptotical Regularization for
                                  Linear Inverse Problems in Presence of
                                  White Noise  . . . . . . . . . . . . . . 1--28
      Johnathan M. Bardsley and   
                   Tiangang Cui   Optimization-Based Markov Chain Monte
                                  Carlo Methods for Nonlinear Hierarchical
                                  Statistical Inverse Problems . . . . . . 29--64
               Ujjwal Koley and   
                   Deep Ray and   
                  Tanmay Sarkar   Multilevel Monte Carlo Finite Difference
                                  Methods for Fractional Conservation Laws
                                  with Random Data . . . . . . . . . . . . 65--105
                  M. Ganesh and   
             Frances Y. Kuo and   
                   Ian H. Sloan   Quasi-Monte Carlo Finite Element
                                  Analysis for Wave Propagation in
                                  Heterogeneous Random Media . . . . . . . 106--134
             Matthew Dobson and   
                     Yao Li and   
                     Jiayu Zhai   Using Coupling Methods to Estimate
                                  Sample Quality of Stochastic
                                  Differential Equations . . . . . . . . . 135--162
          Alen Alexanderian and   
                Noemi Petra and   
              Georg Stadler and   
                  Isaac Sunseri   Optimal Design of Large-scale Bayesian
                                  Linear Inverse Problems Under Reducible
                                  Model Uncertainty: Good to Know What You
                                  Don't Know . . . . . . . . . . . . . . . 163--184
                Amine Hadji and   
            Botond Szabó   Can We Trust Bayesian Uncertainty
                                  Quantification from Gaussian Process
                                  Priors with Squared Exponential
                                  Covariance Kernel? . . . . . . . . . . . 185--230
                   Wenyu Li and   
                 Arun Hegde and   
               James Oreluk and   
             Andrew Packard and   
              Michael Frenklach   Representing Model Discrepancy in
                                  Bound-to-Bound Data Collaboration  . . . 231--259
           Michael Sinsbeck and   
                Emily Cooke and   
                 Wolfgang Nowak   Sequential Design of Computer
                                  Experiments for the Computation of
                                  Bayesian Model Evidence  . . . . . . . . 260--279
          Amal Ben Abdellah and   
            Pierre L'Ecuyer and   
                Art B. Owen and   
             Florian Puchhammer   Density Estimation by Randomized
                                  Quasi-Monte Carlo  . . . . . . . . . . . 280--301
             Takeru Matsuda and   
                  Yuto Miyatake   Estimation of Ordinary Differential
                                  Equation Models with Discretization
                                  Error Quantification . . . . . . . . . . 302--331

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 9, Number 2, 2021

                  Qian Xiao and   
            Abhyuday Mandal and   
               C. Devon Lin and   
                    Xinwei Deng   EzGP: Easy-to-Interpret Gaussian Process
                                  Models for Computer Experiments with
                                  Both Quantitative and Qualitative
                                  Factors  . . . . . . . . . . . . . . . . 333--353
            Philipp A. Guth and   
             Vesa Kaarnioja and   
             Frances Y. Kuo and   
         Claudia Schillings and   
                   Ian H. Sloan   A Quasi-Monte Carlo Method for Optimal
                                  Control Under Uncertainty  . . . . . . . 354--383
              Viet Ha Hoang and   
               Jia Hao Quek and   
               Christoph Schwab   Multilevel Markov Chain Monte Carlo for
                                  Bayesian Inversion of Parabolic Partial
                                  Differential Equations under Gaussian
                                  Prior  . . . . . . . . . . . . . . . . . 384--419
               Henning Omre and   
                Kjartan Rimstad   Bayesian Spatial Inversion and Conjugate
                                  Selection Gaussian Prior Models  . . . . 420--445
            Sebastian Reich and   
                Simon Weissmann   Fokker--Planck Particle Systems for
                                  Bayesian Inference: Computational
                                  Approaches . . . . . . . . . . . . . . . 446--482
                  Wenbo Sun and   
            Matthew Plumlee and   
                 Jingwen Hu and   
            Jionghua (Judy) Jin   Robust System Design with Limited
                                  Experimental Data and an Inexact
                                  Simulation Model . . . . . . . . . . . . 483--506
           Denis Belomestny and   
             Leonid Iosipoi and   
              Eric Moulines and   
              Alexey Naumov and   
                Sergey Samsonov   Variance Reduction for Dependent
                                  Sequences with Applications to
                                  Stochastic Gradient MCMC . . . . . . . . 507--535
               Weifeng Zhao and   
               Juntao Huang and   
                    Wen-An Yong   Lattice Boltzmann Method for Stochastic
                                  Convection--Diffusion Equations  . . . . 536--563
          Antoine Blanchard and   
            Themistoklis Sapsis   Output-Weighted Optimal Sampling for
                                  Bayesian Experimental Design and
                                  Uncertainty Quantification . . . . . . . 564--592
           Nora Lüthen and   
            Stefano Marelli and   
                   Bruno Sudret   Sparse Polynomial Chaos Expansions:
                                  Literature Survey and Benchmark  . . . . 593--649
                 Jingwei Hu and   
           Lorenzo Pareschi and   
                      Yubo Wang   Uncertainty Quantification for the BGK
                                  Model of the Boltzmann Equation Using
                                  Multilevel Variance Reduced Monte Carlo
                                  Methods  . . . . . . . . . . . . . . . . 650--680
María Magdalena Lucini and   
      Peter Jan van Leeuwen and   
                  Manuel Pulido   Model Error Estimation Using the
                                  Expectation Maximization Algorithm and a
                                  Particle Flow Filter . . . . . . . . . . 681--707
                Art B. Owen and   
               Christopher Hoyt   Efficient Estimation of the ANOVA Mean
                                  Dimension, with an Application to Neural
                                  Net Classification . . . . . . . . . . . 708--730
                Vishwas Rao and   
                 Mihai Anitescu   Efficient Computation of Extreme
                                  Excursion Probabilities for Dynamical
                                  Systems through Rice's Formula . . . . . 731--762
              Neil K. Chada and   
              Jordan Franks and   
                 Ajay Jasra and   
                Kody J. Law and   
                   Matti Vihola   Unbiased Inference for Discretely
                                  Observed Hidden Markov Model Diffusions  763--787
         Thomas P. Prescott and   
                  Ruth E. Baker   Multifidelity Approximate Bayesian
                                  Computation with Sequential Monte Carlo
                                  Parameter Sampling . . . . . . . . . . . 788--817
               Felipe Uribe and   
          Iason Papaioannou and   
         Youssef M. Marzouk and   
                  Daniel Straub   Cross-Entropy-Based Importance Sampling
                                  with Failure-Informed Dimension
                                  Reduction for Rare Event Simulation  . . 818--847
                 Ana Djurdjevac   Linear Parabolic Problems in Random
                                  Moving Domains . . . . . . . . . . . . . 848--879
           Jean-Claude Fort and   
              Thierry Klein and   
                Agn\`es Lagnoux   Global Sensitivity Analysis and
                                  Wasserstein Spaces . . . . . . . . . . . 880--921
        Baasansuren Jadamba and   
             Akhtar A. Khan and   
                Miguel Sama and   
        Hans-Jorg Starkloff and   
              Christiane Tammer   A Convex Optimization Framework for the
                                  Inverse Problem of Identifying a Random
                                  Parameter in a Stochastic Partial
                                  Differential Equation  . . . . . . . . . 922--952

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 9, Number 3, 2021

             Daniel Schaden and   
              Elisabeth Ullmann   Asymptotic Analysis of Multilevel Best
                                  Linear Unbiased Estimators . . . . . . . 953--978
            Matthieu Martin and   
                   Fabio Nobile   PDE-Constrained Optimal Control Problems
                                  with Uncertain Parameters using SAGA . . 979--1012
               Zhaopeng Hao and   
               Zhongqiang Zhang   Numerical Approximation of Optimal
                                  Convergence for Fractional Elliptic
                                  Equations with Additive Fractional
                                  Gaussian Noise . . . . . . . . . . . . . 1013--1033
       Christopher Drovandi and   
              David J. Nott and   
             Daniel E. Pagendam   A Semiautomatic Method for History
                                  Matching Using Sequential Monte Carlo    1034--1063
              Amy Braverman and   
             Jonathan Hobbs and   
           Joaquim Teixeira and   
                 Michael Gunson   Post hoc Uncertainty Quantification for
                                  Remote Sensing Observing Systems . . . . 1064--1093
           Deanna C. Easley and   
                    Tyrus Berry   A Higher Order Unscented Transform . . . 1094--1131
             Baptiste Broto and   
     François Bachoc and   
            Marine Depecker and   
             Jean-Marc Martinez   Gaussian Linear Approximation for the
                                  Estimation of the Shapley Effects  . . . 1132--1151
        Valentin Resseguier and   
          Agustin M. Picard and   
              Etienne Memin and   
               Bertrand Chapron   Quantifying Truncation-Related
                                  Uncertainties in Unsteady Fluid Dynamics
                                  Reduced Order Models . . . . . . . . . . 1152--1183
              Alex Bespalov and   
            Dirk Praetorius and   
                Michele Ruggeri   Two-Level a Posteriori Error Estimation
                                  for Adaptive Multilevel Stochastic
                                  Galerkin Finite Element Method . . . . . 1184--1216
                   Wei Fang and   
                  Mike B. Giles   Importance Sampling for Pathwise
                                  Sensitivity of Stochastic Chaotic
                                  Systems  . . . . . . . . . . . . . . . . 1217--1241
            Michal Branicki and   
                    Kenneth Uda   Lagrangian Uncertainty Quantification
                                  and Information Inequalities for
                                  Stochastic Flows . . . . . . . . . . . . 1242--1313
             Dhruv V. Patel and   
                Assad A. Oberai   GAN-Based Priors for Quantifying
                                  Uncertainty in Supervised Learning . . . 1314--1343

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 9, Number 4, 2021

                  Xujia Zhu and   
                   Bruno Sudret   Emulation of Stochastic Simulators Using
                                  Generalized Lambda Models  . . . . . . . 1345--1380
                  Peng Chen and   
                   Omar Ghattas   Taylor Approximation for Chance
                                  Constrained Optimization Problems
                                  Governed by Partial Differential
                                  Equations with High-Dimensional Random
                                  Parameters . . . . . . . . . . . . . . . 1381--1410
             Elmar Plischke and   
           Giovanni Rabitti and   
             Emanuele Borgonovo   Computing Shapley Effects for
                                  Sensitivity Analysis . . . . . . . . . . 1411--1437
            Mahmood Ettehad and   
                  Simon Foucart   Instances of Computational Optimal
                                  Recovery: Dealing with Observation
                                  Errors . . . . . . . . . . . . . . . . . 1438--1456
           Panagiota Birmpa and   
          Markos A. Katsoulakis   Uncertainty Quantification for Markov
                                  Random Fields  . . . . . . . . . . . . . 1457--1498
          Matthew M. Dunlop and   
                     Yunan Yang   Stability of Gibbs Posteriors from the
                                  Wasserstein Loss for Bayesian Full
                                  Waveform Inversion . . . . . . . . . . . 1499--1526
                    Wei Xie and   
                   Cheng Li and   
                 Yuefeng Wu and   
                       Pu Zhang   A Nonparametric Bayesian Framework for
                                  Uncertainty Quantification in Stochastic
                                  Simulation . . . . . . . . . . . . . . . 1527--1552
                 Bangti Jin and   
                 Zehui Zhou and   
                        Jun Zou   On the Saturation Phenomenon of
                                  Stochastic Gradient Descent for Linear
                                  Inverse Problems . . . . . . . . . . . . 1553--1588
               Holger Dette and   
         Anatoly A. Zhigljavsky   Reproducing Kernel Hilbert Spaces,
                                  Polynomials, and the Classical Moment
                                  Problem  . . . . . . . . . . . . . . . . 1589--1614
                  Deyu Ming and   
                  Serge Guillas   Linked Gaussian Process Emulation for
                                  Systems of Computer Models Using Matérn
                                  Kernels and Adaptive Design  . . . . . . 1615--1642
          Jonathan Cockayne and   
                  Andrew Duncan   Probabilistic Gradients for Fast
                                  Calibration of Differential Equation
                                  Models . . . . . . . . . . . . . . . . . 1643--1672
                    Gildas Mazo   A Trade-Off Between Explorations and
                                  Repetitions for Estimators of Two Global
                                  Sensitivity Indices in Stochastic Models
                                  Induced by Probability Measures  . . . . 1673--1713


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 10, Number 1, 2022

           Saumya Bhatnagar and   
                  Won Chang and   
                Seonjin Kim and   
                     Jiali Wang   Computer Model Calibration with Time
                                  Series Data Using Deep Learning and
                                  Quantile Regression  . . . . . . . . . . 1--26
                  John Barr and   
                Herschel Rabitz   A Generalized Kernel Method for Global
                                  Sensitivity Analysis . . . . . . . . . . 27--54
             Louis Sharrock and   
                 Nikolas Kantas   Joint Online Parameter Estimation and
                                  Optimal Sensor Placement for the
                                  Partially Observed Stochastic
                                  Advection--Diffusion Equation  . . . . . 55--95
                H\`a Quang Minh   Finite Sample Approximations of Exact
                                  and Entropic Wasserstein Distances
                                  Between Covariance Operators and
                                  Gaussian Processes . . . . . . . . . . . 96--124
              Devin Francom and   
         Bruno Sansó and   
                 Ana Kupresanin   Landmark-Warped Emulators for Models
                                  with Misaligned Functional Response  . . 125--150
             Teresa Portone and   
                Robert D. Moser   Bayesian Inference of an Uncertain
                                  Generalized Diffusion Operator . . . . . 151--178
           Randolf Altmeyer and   
         Till Bretschneider and   
         Josef Janák and   
              Markus Reiß   Parameter Estimation in an SPDE Model
                                  for Cell Repolarization  . . . . . . . . 179--199
              Michael Giles and   
        Oliver Sheridan-Methven   Analysis of Nested Multilevel Monte
                                  Carlo Using Approximate Normal Random
                                  Variables  . . . . . . . . . . . . . . . 200--226
               Albert Cohen and   
            Wolfgang Dahmen and   
                  Olga Mula and   
                  James Nichols   Nonlinear Reduced Models for State and
                                  Parameter Estimation . . . . . . . . . . 227--267
          Rachel H. Oughton and   
          Michael Goldstein and   
            John C. P. Hemmings   Intermediate Variable Emulation: Using
                                  Internal Processes in Simulators to
                                  Build More Informative Emulators . . . . 268--293
          Hossein Mohammadi and   
            Peter Challenor and   
          Daniel Williamson and   
                Marc Goodfellow   Cross-Validation--based Adaptive
                                  Sampling for Gaussian Process Models . . 294--316
              Fabian Wagner and   
             I. Papaioannou and   
                     E. Ullmann   The Ensemble Kalman Filter for Rare
                                  Event Estimation . . . . . . . . . . . . 317--349
              Amy L. Wilson and   
          Michael Goldstein and   
                  Chris J. Dent   Varying Coefficient Models and Design
                                  Choice for Bayes Linear Emulation of
                                  Complex Computer Models with Limited
                                  Model Evaluations  . . . . . . . . . . . 350--378
             Baptiste Broto and   
     François Bachoc and   
              Laura Clouvel and   
             Jean-Marc Martinez   Block-Diagonal Covariance Estimation and
                                  Application to the Shapley Effects in
                                  Sensitivity Analysis . . . . . . . . . . 379--403
              Sharif Rahman and   
                 Ramin Jahanbin   A Spline Dimensional Decomposition for
                                  Uncertainty Quantification in High
                                  Dimensions . . . . . . . . . . . . . . . 404--438
               Robert Sawko and   
          Ma\lgorzata J. Zimo'n   Effective Generation of Compressed
                                  Stationary Gaussian Fields . . . . . . . 439--452
Charles-Edouard Bréhier and   
                    David Cohen   Strong Rates of Convergence of a
                                  Splitting Scheme for Schrödinger
                                  Equations with Nonlocal Interaction
                                  Cubic Nonlinearity and White Noise
                                  Dispersion . . . . . . . . . . . . . . . 453--480
                Jialei Chen and   
                Zhehui Chen and   
                Chuck Zhang and   
                  C. F. Jeff Wu   APIK: Active Physics-Informed Kriging
                                  Model with Partial Differential
                                  Equations  . . . . . . . . . . . . . . . 481--506
          El Houcine Bergou and   
            Youssef Diouane and   
      Vyacheslav Kungurtsev and   
        Clément W. Royer   A Stochastic Levenberg--Marquardt Method
                                  Using Random Models with Complexity
                                  Results  . . . . . . . . . . . . . . . . 507--536

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 10, Number 2, 2022

          Matthias Katzfuss and   
            Joseph Guinness and   
                  Earl Lawrence   Scaled Vecchia Approximation for Fast
                                  Computer-Model Emulation . . . . . . . . 537--554
              Hassan Arbabi and   
            Themistoklis Sapsis   Generative Stochastic Modeling of
                                  Strongly Nonlinear Flows with
                                  Non-Gaussian Statistics  . . . . . . . . 555--583
              Neil K. Chada and   
                 Ajay Jasra and   
                    Fangyuan Yu   Multilevel Ensemble Kalman--Bucy Filters 584--618
                Wenjia Wang and   
                Xiaowei Yue and   
           Benjamin Haaland and   
                  C. F. Jeff Wu   Gaussian Processes with Input Location
                                  Error and Applications to the Composite
                                  Parts Assembly Process . . . . . . . . . 619--650
                 Josef Dick and   
             Marcello Longo and   
               Christoph Schwab   Extrapolated Polynomial Lattice Rule
                                  Integration in Computational Uncertainty
                                  Quantification . . . . . . . . . . . . . 651--686
              Drew P. Kouri and   
            John D. Jakeman and   
              J. Gabriel Huerta   Risk-Adapted Optimal Experimental Design 687--716
            James M. Salter and   
       Daniel B. Williamson and   
         Lauren J. Gregoire and   
              Tamsin L. Edwards   Quantifying Spatio-Temporal Boundary
                                  Condition Uncertainty for the North
                                  American Deglaciation  . . . . . . . . . 717--744
               Jiahui Zhang and   
                  Anne Gelb and   
               Theresa Scarnati   Empirical Bayesian Inference Using a
                                  Support Informed Prior . . . . . . . . . 745--774
        Alexander M. G. Cox and   
            Simon C. Harris and   
       Andreas E. Kyprianou and   
                    Minmin Wang   Monte Carlo Methods for the Neutron
                                  Transport Equation . . . . . . . . . . . 775--825

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 10, Number 3, 2022

               Pratik Patil and   
             Mikael Kuusela and   
                 Jonathan Hobbs   Objective Frequentist Uncertainty
                                  Quantification for Atmospheric CO$_2$
                                  Retrievals . . . . . . . . . . . . . . . 827--859
            Michael Lindsey and   
             Jonathan Weare and   
                     Anna Zhang   Ensemble Markov Chain Monte Carlo with
                                  Teleporting Walkers  . . . . . . . . . . 860--885
                Shay Gilpin and   
              Tomoko Matsuo and   
                Stephen E. Cohn   Continuum Covariance Propagation for
                                  Understanding Variance Loss in Advective
                                  Systems  . . . . . . . . . . . . . . . . 886--914
            Oliver G. Ernst and   
              Alois Pichler and   
             Björn Sprungk   Wasserstein Sensitivity of Risk and
                                  Uncertainty Propagation  . . . . . . . . 915--948
                  Peijun Li and   
                        Xu Wang   An Inverse Random Source Problem for the
                                  Biharmonic Wave Equation . . . . . . . . 949--974
               Laura Scarabosio   Deep Neural Network Surrogates for
                                  Nonsmooth Quantities of Interest in
                                  Shape Uncertainty Quantification . . . . 975--1011
                  Yuchen He and   
                Namjoon Suh and   
               Xiaoming Huo and   
               Sung Ha Kang and   
                      Yajun Mei   Asymptotic Theory of $
                                  \ell_1$-Regularized PDE Identification
                                  from a Single Noisy Trajectory . . . . . 1012--1036
     Kevin Elie-Dit-Cosaque and   
      Veronique Maume-Deschamps   Goal-Oriented Shapley Effects with
                                  Special Attention to the
                                  Quantile-Oriented Case . . . . . . . . . 1037--1069
             Kody J. H. Law and   
                  Vitaly Zankin   Sparse Online Variational Bayesian
                                  Regression . . . . . . . . . . . . . . . 1070--1100
    Bedrich Sousedík and   
                    Kookjin Lee   Stochastic Galerkin Methods for Linear
                                  Stability Analysis of Systems with
                                  Parametric Uncertainty . . . . . . . . . 1101--1129
             Hamza Ruzayqat and   
              Aimad Er-raiy and   
          Alexandros Beskos and   
                 Dan Crisan and   
                 Ajay Jasra and   
                 Nikolas Kantas   A Lagged Particle Filter for Stable
                                  Filtering of Certain High-Dimensional
                                  State-Space Models . . . . . . . . . . . 1130--1161
              Paul Hagemann and   
          Johannes Hertrich and   
                Gabriele Steidl   Stochastic Normalizing Flows for Inverse
                                  Problems: a Markov Chains Viewpoint  . . 1162--1190
           Paul B. Rohrbach and   
              Sergey Dolgov and   
             Lars Grasedyck and   
                Robert Scheichl   Rank Bounds for Approximating Gaussian
                                  Densities in the Tensor-Train Format . . 1191--1224
           Victor Churchill and   
                      Anne Gelb   Sampling-based Spotlight SAR Image
                                  Reconstruction from Phase History Data
                                  for Speckle Reduction and Uncertainty
                                  Quantification . . . . . . . . . . . . . 1225--1249
                 Trung Pham and   
             Alex A. Gorodetsky   Ensemble Approximate Control Variate
                                  Estimators: Applications to
                                  MultiFidelity Importance Sampling  . . . 1250--1292
               Felipe Uribe and   
      Johnathan M. Bardsley and   
                 Yiqiu Dong and   
       Per Christian Hansen and   
             Nicolai A. B. Riis   A Hybrid Gibbs Sampler for
                                  Edge-Preserving Tomographic
                                  Reconstruction with Uncertain View
                                  Angles . . . . . . . . . . . . . . . . . 1293--1320
              Drew P. Kouri and   
             Thomas M. Surowiec   Corrigendum: Existence and Optimality
                                  Conditions for Risk-Averse
                                  PDE-Constrained Optimization"  . . . 1321--1322

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 10, Number 4, 2022

         Daniel Sanz-Alonso and   
                     Ruiyi Yang   Finite Element Representations of
                                  Gaussian Processes: Balancing Numerical
                                  and Statistical Accuracy . . . . . . . . 1323--1349
            Florian Bourgey and   
             Emmanuel Gobet and   
             Clément Rey   A Comparative Study of Polynomial-Type
                                  Chaos Expansions for Indicator Functions 1350--1383
                   Nan Chen and   
              Quanling Deng and   
               Samuel Stechmann   Superfloe Parameterization with Physics
                                  Constraints for Uncertainty
                                  Quantification of Sea Ice Floes  . . . . 1384--1409
                  Mengqi Hu and   
                  Yifei Lou and   
                       Xiu Yang   A General Framework of Rotational Sparse
                                  Approximation in Uncertainty
                                  Quantification . . . . . . . . . . . . . 1410--1434
                Mengyang Gu and   
              Fangzheng Xie and   
                      Long Wang   A Theoretical Framework of the Scaled
                                  Gaussian Stochastic Process in
                                  Prediction and Calibration . . . . . . . 1435--1460
           Panagiota Birmpa and   
               Jinchao Feng and   
      Markos A. Katsoulakis and   
                 Luc Rey-Bellet   Model Uncertainty and Correctability for
                                  Directed Graphical Models  . . . . . . . 1461--1512
                 Yifei Wang and   
                  Peng Chen and   
                      Wuchen Li   Projected Wasserstein Gradient Descent
                                  for High-Dimensional Bayesian Inference  1513--1532
               Shiv Agrawal and   
                Hwanwoo Kim and   
          Danie Sanz-Alonso and   
               Alexander Strang   A Variational Inference Approach to
                                  Inverse Problems with Gamma Hyperpriors  1533--1559
   Ömer Deniz Akyildiz and   
              Connor Duffin and   
           Sotirios Sabanis and   
                  Mark Girolami   Statistical Finite Elements via Langevin
                                  Dynamics . . . . . . . . . . . . . . . . 1560--1585
              Thierry Klein and   
            Nicolas Peteilh and   
                    Paul Rochet   Test Comparison for Sobol Indices over
                                  Nested Sets of Variables . . . . . . . . 1586--1600
            Marcus J. Grote and   
               Simon Michel and   
                   Fabio Nobile   Uncertainty Quantification by Multilevel
                                  Monte Carlo and Local Time-Stepping for
                                  Wave Propagation . . . . . . . . . . . . 1601--1628
                 Zilong Zou and   
              Drew P. Kouri and   
                 Wilkins Aquino   A Locally Adapted Reduced-Basis Method
                                  for Solving Risk-Averse PDE-Constrained
                                  Optimization Problems  . . . . . . . . . 1629--1651
                       Yan Wang   Penalized Projected Kernel Calibration
                                  for Computer Models  . . . . . . . . . . 1652--1683
                 Shiwei Lan and   
                   Shuyi Li and   
                 Babak Shahbaba   Scaling Up Bayesian Uncertainty
                                  Quantification for Inverse Problems
                                  Using Deep Neural Networks . . . . . . . 1684--1713
                   Moyan Li and   
                    Raed Kontar   On Negative Transfer and Structure of
                                  Latent Functions in Multioutput Gaussian
                                  Processes  . . . . . . . . . . . . . . . 1714--1732
               Chih-Li Sung and   
          Beau David Barber and   
              Berkley J. Walker   Calibration of Inexact Computer Models
                                  with Heteroscedastic Errors  . . . . . . 1733--1752
              Tobias Jahnke and   
                    Benny Stein   A Multilevel Stochastic Collocation
                                  Method for Schrödinger Equations with a
                                  Random Potential . . . . . . . . . . . . 1753--1780


SIAM\slash ASA Journal on Uncertainty Quantification
Volume 11, Number 1, 2023

           M. B. Lykkegaard and   
              T. J. Dodwell and   
                     C. Fox and   
                  G. Mingas and   
                    R. Scheichl   Multilevel Delayed Acceptance MCMC . . . 1--30
       Babak Maboudi Afkham and   
                 Yiqiu Dong and   
           Per Christian Hansen   Uncertainty Quantification of Inclusion
                                  Boundaries in the Context of X-Ray
                                  Tomography . . . . . . . . . . . . . . . 31--61
                 Wouter Edeling   On the Deep Active-Subspace Method . . . 62--90
    Juan P. Madrigal-Cianci and   
               Fabio Nobile and   
            Raúl Tempone   Analysis of a Class of Multilevel Markov
                                  Chain Monte Carlo Algorithms Based on
                                  Independent Metropolis--Hastings . . . . 91--138
                Martin Chak and   
             Nikolas Kantas and   
         Grigorios A. Pavliotis   On the Generalized Langevin Equation for
                                  Simulated Annealing  . . . . . . . . . . 139--167
  Cédric Travelletti and   
          David Ginsbourger and   
                   Niklas Linde   Uncertainty Quantification and
                                  Experimental Design for Large-Scale
                                  Linear Inverse Problems under Gaussian
                                  Process Priors . . . . . . . . . . . . . 168--198
           Christoph Schwab and   
                     Jakob Zech   Deep Learning in High Dimension: Neural
                                  Network Expression Rates for Analytic
                                  Functions in $ L^2 (\mathbb {R}^d,
                                  \gamma_d) $  . . . . . . . . . . . . . . 199--234
                    Keyi Wu and   
                  Peng Chen and   
                   Omar Ghattas   A Fast and Scalable Computational
                                  Framework for Large-Scale
                                  High-Dimensional Bayesian Optimal
                                  Experimental Design  . . . . . . . . . . 235--261
               Jan Glaubitz and   
                  Anne Gelb and   
                    Guohui Song   Generalized Sparse Bayesian Learning and
                                  Application to Image Reconstruction  . . 262--284
             Terrence Alsup and   
          Benjamin Peherstorfer   Context-Aware Surrogate Modeling for
                                  Balancing Approximation and Sampling
                                  Costs in Multifidelity Importance
                                  Sampling and Bayesian Inverse Problems   285--319
               Leon Bungert and   
                 Philipp Wacker   Complete Deterministic Dynamics and
                                  Spectral Decomposition of the Linear
                                  Ensemble Kalman Inversion  . . . . . . . 320--357
                   Max Ehre and   
               Rafael Flock and   
       Martin Fußeder and   
          Iason Papaioannou and   
                  Daniel Straub   Certified Dimension Reduction for
                                  Bayesian Updating with the Cross-Entropy
                                  Method . . . . . . . . . . . . . . . . . 358--388

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 11, Number 2, 2023

           Adrian N. Bishop and   
               Pierre Del Moral   Robust Kalman and Bayesian Set-Valued
                                  Filtering and Model Validation for
                                  Linear Stochastic Systems  . . . . . . . 389--425
Christophette Blanchet-Scalliet and   
               Bruno Demory and   
              Thierry Gonon and   
          Céline Helbert   Gaussian Process Regression on Nested
                                  Spaces . . . . . . . . . . . . . . . . . 426--451
            Fedor Goncharov and   
          Éric Barat and   
               Thomas Dautremer   Nonparametric Posterior Learning for
                                  Emission Tomography  . . . . . . . . . . 452--479
         Maarten V. de Hoop and   
         Nikola B. Kovachki and   
         Nicholas H. Nelsen and   
               Andrew M. Stuart   Convergence Rates for Learning Linear
                                  Operators from Noisy Data  . . . . . . . 480--513
             Baptiste Kerleguer   Multifidelity Surrogate Modeling for
                                  Time-Series Outputs  . . . . . . . . . . 514--539
          Elaine T. Spiller and   
          Robert L. Wolpert and   
                Pablo Tierz and   
                Taylor G. Asher   The Zero Problem: Gaussian Process
                                  Emulators for Range-Constrained Computer
                                  Models . . . . . . . . . . . . . . . . . 540--566
               E. A. Spence and   
                      J. Wunsch   Wavenumber-Explicit Parametric
                                  Holomorphy of Helmholtz Solutions in the
                                  Context of Uncertainty Quantification    567--590
                       Tim Jahn   Noise Level Free Regularization of
                                  General Linear Inverse Problems under
                                  Unconstrained White Noise  . . . . . . . 591--615
                Jeremy Heng and   
                 Ajay Jasra and   
             Kody J. H. Law and   
            Alexander Tarakanov   On Unbiased Estimation for Discretized
                                  Models . . . . . . . . . . . . . . . . . 616--645
                Ben Mansour Dia   A Continuation Method in Bayesian
                                  Inference  . . . . . . . . . . . . . . . 646--681
                  Yian Chen and   
                 Mihai Anitescu   Scalable Physics-Based Maximum
                                  Likelihood Estimation Using Hierarchical
                                  Matrices . . . . . . . . . . . . . . . . 682--725

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 11, Number 3, 2023

               Prerna Patil and   
                  Hessam Babaee   Reduced-Order Modeling with
                                  Time-Dependent Bases for PDEs with
                                  Stochastic Boundary Conditions . . . . . 727--756
         Claudia Schillings and   
            Claudia Totzeck and   
                 Philipp Wacker   Ensemble-Based Gradient Inference for
                                  Particle Methods in Optimization and
                                  Sampling . . . . . . . . . . . . . . . . 757--787
               Shanyin Tong and   
                  Georg Stadler   Large Deviation Theory-based Adaptive
                                  Importance Sampling for Rare Events in
                                  High Dimensions  . . . . . . . . . . . . 788--813
              Elliot Cartee and   
              Antonio Farah and   
               April Nellis and   
             Jacob Van Hook and   
          Alexander Vladimirsky   Quantifying and Managing Uncertainty in
                                  Piecewise-Deterministic Markov Processes 814--847
   Cécile Haberstich and   
                    A. Nouy and   
                      G. Perrin   Active Learning of Tree Tensor Networks
                                  using Optimal Least Squares  . . . . . . 848--876
         Christophe Audouze and   
                Aaron Klein and   
            Adrian Butscher and   
               Nigel Morris and   
              Prasanth Nair and   
                  Masayuki Yano   Robust Level-Set-Based Topology
                                  Optimization Under Uncertainties Using
                                  Anchored ANOVA Petrov--Galerkin Method   877--905
                  Sam Allen and   
          David Ginsbourger and   
                 Johanna Ziegel   Evaluating Forecasts for High-Impact
                                  Events Using Transformed Kernel Scores   906--940
             Alexey Chernov and   
             Erik Marc Schetzke   A Simple, Bias-free Approximation of
                                  Covariance Functions by the Multilevel
                                  Monte Carlo Method Having Nearly Optimal
                                  Complexity . . . . . . . . . . . . . . . 941--969
                Teo Deveney and   
            Eike H. Mueller and   
                  Tony Shardlow   Deep Surrogate Accelerated
                                  Delayed-Acceptance Hamiltonian Monte
                                  Carlo for Bayesian Inference of
                                  Spatio-Temporal Heat Fluxes in Rotating
                                  Disc Systems . . . . . . . . . . . . . . 970--995
        Nathaniel Pritchard and   
                    Vivak Patel   Towards Practical Large-Scale Randomized
                                  Iterative Least Squares Solvers through
                                  Uncertainty Quantification . . . . . . . 996--1024
          Jasper M. Everink and   
                 Yiqiu Dong and   
             Martin S. Andersen   Bayesian Inference with Projected
                                  Densities  . . . . . . . . . . . . . . . 1025--1043
              Vladimir Spokoiny   Dimension Free Nonasymptotic Bounds on
                                  the Accuracy of High-Dimensional Laplace
                                  Approximation  . . . . . . . . . . . . . 1044--1068
                  Shurui Lv and   
                     Jun Yu and   
                   Yan Wang and   
                       Jiang Du   Fast Calibration for Computer Models
                                  with Massive Physical Observations . . . 1069--1104

SIAM\slash ASA Journal on Uncertainty Quantification
Volume 11, Number 4, 2023

               Remo Kretschmann   Are Minimizers of the Onsager--Machlup
                                  Functional Strong Posterior Modes? . . . 1105--1138