Energy-dissipative evolutionary deep operator neural networks-Reference-Cited by-同舟云学术

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Energy-dissipative evolutionary deep operator neural networks

Published:2024-02 Issue: Volume:498 Page:112638
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Zhang Jiahao,Zhang Shiheng,Shen Jie,Lin Guang^ORCID

Funder

National Natural Science Foundation of China

National Science Foundation

U.S. Department of Energy

Air Force Office of Scientific Research

Advanced Scientific Computing Research

Fusion Energy Sciences

Publisher

Elsevier BV

Subject

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

Reference35 articles.

1. Solving parametric pde problems with artificial neural networks;Khoo;Eur. J. Appl. Math.,2021

2. The random feature model for input-output maps between banach spaces;Nelsen;SIAM J. Sci. Comput.,2021

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