Variational inference for nonlinear inverse problems via neural net kernels: Comparison to Bayesian neural networks, application to topology optimization-Reference-Cited by-同舟云学术

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Variational inference for nonlinear inverse problems via neural net kernels: Comparison to Bayesian neural networks, application to topology optimization

Published:2022-10 Issue: Volume:400 Page:115495
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:

Keshavarzzadeh Vahid^ORCID,Kirby Robert M.,Narayan Akil^ORCID

Funder

Army Research Laboratory

Air Force Office of Scientific Research

Defense Advanced Research Projects Agency

Publisher

Elsevier BV

Subject

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

Reference68 articles.

1. Bayesian Data Analysis;Gelman,2013

2. Monte Carlo Strategies in Scientific Computing;Liu,2004

3. MCMC using Hamiltonian Dynamics;Neal,2011

4. Pattern Recognition and Machine Learning;Bishop,2013

5. Weight uncertainty in neural networks;Blundell,2015

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1. Using conditional normalizing flows to generate material placements in an optimized thermal composite;International Journal of Heat and Mass Transfer;2024-06

2. INVERSION METHOD OF UNCERTAIN PARAMETERS FOR TRUSS STRUCTURES BASED ON GRAPH NEURAL NETWORKS;ADV STEEL CONSTR;2023-12-01

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