Surrogate modeling for Bayesian inverse problems based on physics-informed neural networks-Reference-Cited by-同舟云学术

Surrogate modeling for Bayesian inverse problems based on physics-informed neural networks

Published:2023-02 Issue: Volume:475 Page:111841
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Li Yongchao,Wang Yanyan,Yan Liang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Physics and Astronomy (miscellaneous),Applied Mathematics,Computational Mathematics,Modeling and Simulation,Numerical Analysis

Reference41 articles.

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2. Computational Methods for Inverse Problems;Vogel,2002

3. Statistical and Computational Inverse Problems;Kaipio,2005

4. Inverse problems: a Bayesian perspective;Stuart;Acta Numer.,2010

5. Handbook of Markov Chain Monte Carlo;Yanan,2011

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