Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

DOI10.1016/j.jcp.2013.10.001zbMath1349.76815OpenAlexW2014638166MaRDI QIDQ348583

Ibrahim Hoteit, Ahmed H. Elsheikh, Mary Fanett Wheeler

Publication date: 5 December 2016

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

Full work available at URL: https://doi.org/10.1016/j.jcp.2013.10.001

zbMATH Keywords

hybrid Monte Carlouncertainty quantificationnested samplingBayesian model comparisonstochastic ensemble methodsubsurface flow models

Mathematics Subject Classification ID

Gaussian processes (60G15) Bayesian inference (62F15) Monte Carlo methods (65C05) Flows in porous media; filtration; seepage (76S05) Homogenization applied to problems in fluid mechanics (76M50)

Related Items (4)

Bayesian inversion using adaptive polynomial chaos kriging within subset simulation ⋮ Bayesian analysis of rare events ⋮ Coordinate transformation and polynomial chaos for the Bayesian inference of a Gaussian process with parametrized prior covariance function ⋮ Efficient estimation of hydraulic conductivity heterogeneity with non-redundant measurement information

Uses Software

• CosmoNest

Cites Work

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