Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems
DOI10.1137/17M1137218zbMath1401.65040arXiv1609.07180OpenAlexW2883157112WikidataQ129495354 ScholiaQ129495354MaRDI QIDQ4689166
D. Andrew Brown, Arvind K. Saibaba, Sarah Vallélian
Publication date: 15 October 2018
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1609.07180
computerized tomographylow-rank approximationimage deblurringMetropolis-Hastings independence samplerprior-preconditioned Hessian
Ill-posedness and regularization problems in numerical linear algebra (65F22) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)
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