Název: Numerical realization of the Bayesian inversion accelerated using surrogate models
Autoři: Bérešová, Simona
Typ dokumentu: Příspěvky z konference
Konference/Akce: Programs and Algorithms of Numerical Mathematics /21./, Jablonec nad Nisou (CZ), 20220619
Rok: 2023
Jazyk: eng
Abstrakt: The Bayesian inversion is a natural approach to the solution of inverse problems based on uncertain observed data. The result of such an inverse problem is the posterior distribution of unknown parameters. This paper deals with the numerical realization of the Bayesian inversion focusing on problems governed by computationally expensive forward models such as numerical solutions of partial differential equations. Samples from the posterior distribution are generated using the Markov chain Monte Carlo (MCMC) methods accelerated with surrogate models. A surrogate model is understood as an approximation of the forward model which should be computationally much cheaper. The target distribution is not fully replaced by its approximation. Therefore, samples from the exact posterior distribution are provided. In addition, non-intrusive surrogate models can be updated during the sampling process resulting in an adaptive MCMC method. The use of the surrogate models significantly reduces the number of evaluations of the forward model needed for a reliable description of the posterior distribution. Described sampling procedures are implemented in the form of a Python package.
Klíčová slova: Bayesian inversion; delayed-acceptance Metropolis-Hastings; Markov chain Monte Carlo; surrogate model
Číslo projektu: TK02010118
Poskytovatel projektu: GA TA ČR
Zdrojový dokument: Programs and Algorithms of Numerical Mathematics 21 : Proceedings of Seminar, ISBN 978-80-85823-73-8

Instituce: Ústav geoniky AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: https://dml.cz/bitstream/handle/10338.dmlcz/703185/PANM_21-2022-1_6.pdf
Původní záznam: https://hdl.handle.net/11104/0342777

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-524977


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