A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations-Reference-Cited by-同舟云学术

A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations

Published:2022-08 Issue: Volume:462 Page:111260
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Yuan Lei,Ni Yi-Qing^ORCID,Deng Xiang-Yun,Hao Shuo

Publisher

Elsevier BV

Subject

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

Reference64 articles.

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2. Automatic differentiation in machine learning: a survey;Baydin;J. Mach. Learn. Res.,2018

3. Physics-informed neural networks (PINNs) for fluid mechanics: a review;Cai;Acta Mech. Sin.,2022

4. Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport;He;Adv. Water Resour.,2020

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