Last update: Mon Aug 26 12:49:24 MDT 2024
Volume 1, Number 1, 2013James 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Remo Kretschmann Are Minimizers of the Onsager--Machlup Functional Strong Posterior Modes? . . . 1105--1138 Johannes Milz Reliable Error Estimates for Optimal Control of Linear Elliptic PDEs with Random Inputs . . . . . . . . . . . . . 1139--1163 Yao Li and Yaping Yuan Sensitivity Analysis of Quasi-Stationary Distributions (QSDs) of Mass-Action Systems . . . . . . . . . . . . . . . . 1164--1194 Hefin Lambley and T. J. Sullivan An Order-Theoretic Perspective on Modes and Maximum A Posteriori Estimation in Bayesian Inverse Problems . . . . . . . 1195--1224 Toni Karvonen Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolation . . . . . . . . . . . . . 1225--1257 Vilho Halonen and Ilkka Pölönen Quantification of Errors Generated by Uncertain Data in a Linear Boundary Value Problem Using Neural Networks . . 1258--1277 Yanni Papandreou and Jon Cockayne and Mark Girolami and Andrew Duncan Theoretical Guarantees for the Statistical Finite Element Method . . . 1278--1307 Sébastien J. Petit and Julien Bect and Paul Feliot and Emmanuel Vazquez Parameter Selection in Gaussian Process Interpolation: An Empirical Study of Selection Criteria . . . . . . . . . . . 1308--1328 Seif Ben Bader and Helmut Harbrecht and Rolf Krause and Michael D. Multerer and Alessio Quaglino and Marc Schmidlin Space-time Multilevel Quadrature Methods and their Application for Cardiac Electrophysiology . . . . . . . . . . . 1329--1356 Suraj Yerramilli and Akshay Iyer and Wei Chen and Daniel W. Apley Fully Bayesian Inference for Latent Variable Gaussian Process Models . . . . 1357--1381
Zhizhang Wu and Zhiwen Zhang and Xiaofei Zhao Error Estimate of a Quasi-Monte Carlo Time-Splitting Pseudospectral Method for Nonlinear Schrödinger Equation with Random Potentials . . . . . . . . . . . 1--29 Daniel Sanz-Alonso and Nathan Waniorek Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement . . . . . . . . . . . . 30--68 Jed A. Duersch Projective Integral Updates for High-Dimensional Variational Inference 69--100 Xianliang Gong and Yulin Pan Multifidelity Bayesian Experimental Design to Quantify Rare-Event Statistics 101--127 Guillaume Chennetier and Hassane Chraibi and Anne Dutfoy and Josselin Garnier Adaptive Importance Sampling Based on Fault Tree Analysis for Piecewise Deterministic Markov Process . . . . . . 128--156 Chih-Li Sung and Ji, Yi (Irene) and Simon Mak and Wenjia Wang and Tao Tang Stacking Designs: Designing Multifidelity Computer Experiments with Target Predictive Accuracy . . . . . . . 157--181 Ningxin Liu and Lijian Jiang Perron--Frobenius Operator Filter for Stochastic Dynamical Systems . . . . . . 182--211 M. Ganesh and Frances Y. Kuo and Ian H. Sloan Corrigendum: Quasi--Monte Carlo Finite Element Analysis for Wave Propagation in Heterogeneous Random Media . . . . . . . 212--212
Nuojin Cheng and Osman Asif Malik and Yiming Xu and Stephen Becker and Alireza Doostan and Akil Narayan Subsampling of Parametric Models with Bifidelity Boosting . . . . . . . . . . 213--241 Jacob Curran-Sebastian and Lorenzo Pellis and Ian Hall and Thomas House Calculation of Epidemic First Passage and Peak Time Probability Distributions 242--261 Grigorios A. Pavliotis and Andrea Zanoni A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit . . . . . . . . . . . . 262--288 Rafael Ballester-Ripoll Computing Statistical Moments Via Tensorization of Polynomial Chaos Expansions . . . . . . . . . . . . . . . 289--308 Carsten Hartmann and Lorenz Richter Nonasymptotic Bounds for Suboptimal Importance Sampling . . . . . . . . . . 309--346 Konstantin Häberle and Barbara Bravi and Anthea Monod Wavelet-Based Density Estimation for Persistent Homology . . . . . . . . . . 347--376 Fabienne Comte and Valentine Genon-Catalot Nonparametric Estimation for Independent and Identically Distributed Stochastic Differential Equations with Space-Time Dependent Coefficients . . . . . . . . . 377--410 Omar Al-Ghattas and Jiajun Bao and Daniel Sanz-Alonso Ensemble Kalman Filters with Resampling 411--441 Jan Glaubitz and Anne Gelb Leveraging Joint Sparsity in Hierarchical Bayesian Learning . . . . . 442--472 Yi Ji and Henry Shaowu Yuchi and Derek Soeder and J.-F. Paquet and Steffen A. Bass and V. Roshan Joseph and C. F. Jeff Wu and Simon Mak Conglomerate Multi-fidelity Gaussian Process Modeling, with Application to Heavy-Ion Collisions . . . . . . . . . . 473--502 Helmut Harbrecht and Viacheslav Karnaev and Marc Schmidlin Quantifying Domain Uncertainty in Linear Elasticity . . . . . . . . . . . . . . . 503--523 D. Calvetti and E. Somersalo Computationally Efficient Sampling Methods for Sparsity Promoting Hierarchical Bayesian Models . . . . . . 524--548 Qin Li and Li Wang and Yunan Yang Differential Equation-Constrained Optimization with Stochasticity . . . . 524--548 Jianbo Cui and Liying Sun Quantifying the Effect of Random Dispersion for Logarithmic Schrödinger Equation . . . . . . . . . . . . . . . . 579--613 Philipp A. Guth and Claudia Schillings and Simon Weissmann One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty . . . . . . . . . . . . . . 614--645 Kellin N. Rumsey and Devin Francom and Andy Shen Generalized Bayesian MARS: Tools for Stochastic Computer Model Emulation . . 646--666 Margot Herin and Marouane Il Idrissi and Vincent Chabridon and Bertrand Iooss Proportional Marginal Effects for Global Sensitivity Analysis . . . . . . . . . . 667--692 Fabio Nobile and Tommaso Vanzan A Combination Technique for Optimal Control Problems Constrained by Random PDEs . . . . . . . . . . . . . . . . . . 693--721
Nada Cvetkovi\'c and Han Cheng Lie and Harshit Bansal and Karen Veroy Choosing Observation Operators to Mitigate Model Error in Bayesian Inverse Problems . . . . . . . . . . . . . . . . 723--758 Feng Yu and Lixin Shen and Guohui Song Hyperparameter Estimation for Sparse Bayesian Learning Models . . . . . . . . 759--787 Hossein Mohammadi and Peter Challenor and Marc Goodfellow Emulating Complex Dynamical Simulators with Random Fourier Features . . . . . . 788--811 Liu Liu and Kunlun Qi Spectral Convergence of a Semi-discretized Numerical System for the Spatially Homogeneous Boltzmann Equation with Uncertainties . . . . . . 812--841 Mircea Grigoriu Harmonizable Nonstationary Processes . . 842--867 Ricardo Baptista and Bamdad Hosseini and Nikola B. Kovachki and Youssef M. Marzouk Conditional Sampling with Monotone GANs: From Generative Models to Likelihood-Free Inference . . . . . . . 868--900 Niklas Baumgarten and Sebastian Krumscheid and Christian Wieners A Fully Parallelized and Budgeted Multilevel Monte Carlo Method and the Application to Acoustic Waves . . . . . 901--931 D. Elfverson and R. Scheichl and S. Weissmann and F. A. Diaz De La O Adaptive Multilevel Subset Simulation with Selective Refinement . . . . . . . 932--963