On global normal linear approximations for nonlinear Bayesian inverse problems

DOI10.1088/1361-6420/acc129OpenAlexW4323034567MaRDI QIDQ5886385

Noemi Petra, R. Nicholson, Umberto Villa, Jari P. Kaipio

Publication date: 5 April 2023

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1088/1361-6420/acc129

zbMATH Keywords

linear approximationBayesian inferencemodel errorsuncertainty quantificationBayesian approximation errorsinverse problems governed by PDEs

Mathematics Subject Classification ID

Numerical analysis (65-XX) Miscellaneous topics in partial differential equations (35Rxx)

Cites Work

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• An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
• Whittle-Matérn priors for Bayesian statistical inversion with applications in electrical impedance tomography
• Approximation errors in nonstationary inverse problems
• Statistical and computational inverse problems.
• Recovery from errors due to domain truncation in magnetic particle imaging: approximation error modeling approach
• Global uniqueness for a two-dimensional inverse boundary value problem
• An additive approximation to multiplicative noise
• Calderón's inverse conductivity problem in the plane
• An introduction to infinite-dimensional analysis
• Statistical inverse problems: discretization, model reduction and inverse crimes
• Bayesian Calibration of Computer Models
• Inverse problems: A Bayesian perspective
• Learning about physical parameters: the importance of model discrepancy
• A Bayesian-based approach to improving acoustic Born waveform inversion of seismic data for viscoelastic media
• Approximation errors and model reduction with an application in optical diffusion tomography
• Erratum: A nonlinear approach to difference imaging in EIT; assessment of the robustness in the presence of modelling errors (2015 Inverse Problems 31 035012)
• Newton regularizations for impedance tomography: convergence by local injectivity
• The regularization of incorrect problems with an approximately specified operator
• Recent Developments in Inverse Acoustic Scattering Theory
• Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization
• Variational Gaussian approximation for Poisson data
• Iterative updating of model error for Bayesian inversion
• Linear and Nonlinear Inverse Problems with Practical Applications
• Combining Field Data and Computer Simulations for Calibration and Prediction
• Estimation of the Robin coefficient field in a Poisson problem with uncertain conductivity field
• Electrical impedance tomography
• On the local Lipschitz stability of Bayesian inverse problems
• A Bayesian approach to improving the Born approximation for inverse scattering with high-contrast materials
• Inverse Acoustic and Electromagnetic Scattering Theory
• A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion
• Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review
• On Learned Operator Correction in Inverse Problems
• An introduction to the mathematical theory of inverse problems

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