Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

DOI10.1016/j.jcp.2008.11.024zbMath1161.65308OpenAlexW2074686342MaRDI QIDQ1009939

Habib N. Najm, Youssef M. Marzouk

Publication date: 3 April 2009

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1721.1/59814

zbMATH Keywords

numerical examplesGaussian processesinverse problemsMarkov chain Monte CarloBayesian inferencedimensionality reductionreproducing kernel Hilbert spaceGalerkin projectionpolynomial chaosKarhunen-Loève expansion

Mathematics Subject Classification ID

Inverse problems for PDEs (35R30) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22)

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Uses Software

• RKC
• BayesDA

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