Probabilistic learning inference of boundary value problem with uncertainties based on Kullback–Leibler divergence under implicit constraints-Reference-Cited by-同舟云学术

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Probabilistic learning inference of boundary value problem with uncertainties based on Kullback–Leibler divergence under implicit constraints

Published:2022-05 Issue: Volume:395 Page:115078
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Soize Christian^ORCID

Publisher

Elsevier BV

Subject

Computer Science Applications,General Physics and Astronomy,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Reference151 articles.

1. Bayesian Theory;Bernardo,2000

2. Bayesian calibration of computer models;Kennedy;J. R. Stat. Soc. Ser. B Stat. Methodol.,2001

3. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control, Vol. 65;Spall,2005

4. Bayesian Statistical Modelling, Vol. 704;Congdon,2007

5. Bayesian Methods for Data Analysis;Carlin,2008

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