A Bayesian approach to multiscale inverse problems using the sequential Monte Carlo method

DOI10.1088/0266-5611/27/10/105004zbMath1228.65009OpenAlexW2128878127MaRDI QIDQ3097931

Nicholas Zabaras, Jiang Wan

Publication date: 10 November 2011

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

Full work available at URL: https://doi.org/10.1088/0266-5611/27/10/105004

zbMATH Keywords

comparison of methodsparameter estimationnumerical examplesMarkov chain Monte Carlo methodsmultiple scalesadaptive refinement strategyflows through porous mediasequential Monte Carlo samplerBayesian computational approach

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15) Monte Carlo methods (65C05) Flows in porous media; filtration; seepage (76S05) Stochastic analysis applied to problems in fluid mechanics (76M35) Numerical analysis or methods applied to Markov chains (65C40)

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