Choosing observation operators to mitigate model error in Bayesian inverse problems
type: Item
instance of: scholarly article
title: Choosing observation operators to mitigate model error in Bayesian inverse problems
zbMATH Open document ID: 1543.6229
author: Nada Cvetković
author: Han Cheng Lie
author: Harshit Bansal
author: Karen Veroy
published in: SIAM/ASA Journal on Uncertainty Quantification
publication date: 2024-08-14T00:00:00Z
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62K05
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 35R30
zbMATH DE Number: 7896958
zbMATH Keywords: model error
zbMATH Keywords: Bayesian inverse problems
zbMATH Keywords: experimental design
zbMATH Keywords: misspecified likelihood
zbMATH Keywords: posterior error bounds
MaRDI profile type: Publication
cites work: Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration
cites work: A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized $\ell_0$-Sparsification
cites work: Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know
cites work: Learning about physical parameters: the importance of model discrepancy
cites work: Iterative updating of model error for Bayesian inversion
cites work: Residual-based error correction for neural operator accelerated Infinite-dimensional Bayesian inverse problems
cites work: Inversion of a perturbed matrix
cites work: Stability estimates for the expected utility in Bayesian optimal experimental design
cites work: Finite elements and fast iterative solvers. With applications in incompressible fluid dynamics
cites work: Fundamentals of Nonparametric Bayesian Inference
cites work: How Biased Is Your Model? Concentration Inequalities, Information and Model Bias
cites work: Robust Information Divergences for Model-Form Uncertainty Arising from Sparse Data in Random PDE
cites work: Q4421310
cites work: Statistical and computational inverse problems.
cites work: Statistical inverse problems: discretization, model reduction and inverse crimes
cites work: Bayesian calibration of computer models. (With discussion)
cites work: MARGINALIZATION OF UNINTERESTING DISTRIBUTED PARAMETERS IN INVERSE PROBLEMS APPLICATION TO DIFFUSE OPTICAL TOMOGRAPHY
cites work: Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs
cites work: Automated solution of differential equations by the finite element method. The FEniCS book
cites work: Adaptive PBDW Approach to State Estimation: Noisy Observations; User-Defined Update Spaces
cites work: Estimation of the Robin coefficient field in a Poisson problem with uncertain conductivity field
cites work: Numerical models for differential problems
cites work: EMBEDDED MODEL ERROR REPRESENTATION FOR BAYESIAN MODEL CALIBRATION
cites work: On the local Lipschitz stability of Bayesian inverse problems
cites work: Inverse problems: a Bayesian perspective
cites work: hIPPYlib
cites work: High-Dimensional Statistics
DOI: 10.1137/23M1602140
description: scientific article; zbMATH DE number 7896958