Multilevel Markov Chain Monte Carlo for Bayesian Inversion of Parabolic Partial Differential Equations under Gaussian Prior

DOI10.1137/20M1354714zbMath1465.65006OpenAlexW3152645313WikidataQ115246886 ScholiaQ115246886MaRDI QIDQ4995109

Viet Hà Hoàng, Christoph Schwab, Jia Hao Quek

Publication date: 23 June 2021

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/20m1354714

zbMATH Keywords

parabolic equationsGaussian priorBayesian inversionmultilevel Markov chain Monte Carlolog-normal coefficientsessentially optimal complexity

Mathematics Subject Classification ID

Random fields (60G60) Monte Carlo methods (65C05) 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)

Related Items (3)

Bayesian inversion of log-normal eikonal equations ⋮ Analysis of RHC for Stabilization of Nonautonomous Parabolic Equations Under Uncertainty ⋮ Multilevel Markov chain Monte Carlo for Bayesian inverse problem for Navier-Stokes equation

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