MCMC Algorithms for Computational UQ of Nonnegativity Constrained Linear Inverse Problems

DOI10.1137/18M1234588zbMath1442.65031MaRDI QIDQ5112550

Per Christian Hansen, Johnathan M. Bardsley

Publication date: 29 May 2020

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

zbMATH Keywords

inverse problemsMarkov chain Monte CarloBayesian methodsuncertainty quantificationnonnegativity constraints

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Inverse problems in linear algebra (15A29) Direct numerical methods for linear systems and matrix inversion (65F05)

Related Items (3)

Bayesian Inference with Projected Densities ⋮ Efficient Bayesian Computation for Low-Photon Imaging Problems ⋮ A statistical reconstruction model for absorption CT with source uncertainty ^*

Uses Software

• GMRFLib
• BayesDA

Cites Work

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• Gaussian Markov Random Fields
• The Spike-and-Slab LASSO
• Discrete Inverse Problems
• Introduction to Bayesian Scientific Computing
• MCMC methods for functions: modifying old algorithms to make them faster

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