Zero coordinate shift: Whetted automatic differentiation for physics-informed operator learning-Reference-Cited by-同舟云学术

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Zero coordinate shift: Whetted automatic differentiation for physics-informed operator learning

Published:2024-05 Issue: Volume:505 Page:112904
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Leng Kuangdai^ORCID,Shankar Mallikarjun,Thiyagalingam Jeyan^ORCID

Funder

EPSRC

Publisher

Elsevier BV

Reference49 articles.

1. Physics-informed machine learning;Karniadakis;Nat. Rev. Phys.,2021

2. Scientific machine learning through physics-informed neural networks: where we are and what's next;Cuomo;J. Sci. Comput.,2022

3. Physics-informed generative adversarial networks for stochastic differential equations;Yang;SIAM J. Sci. Comput.,2020

4. A-PINN: auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations;Yuan;J. Comput. Phys.,2022

5. fPINNs: fractional physics-informed neural networks;Pang;SIAM J. Sci. Comput.,2019

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