CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method
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Title
CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method
Authors
Keywords
Physics-informed neural network, Training loss formulation, Taylor series expansions, Coupled-automatic–numerical differentiation, Navier–Stokes equations, Inverse problem
Journal
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
Volume 395, Issue -, Pages 114909
Publisher
Elsevier BV
Online
2022-04-28
DOI
10.1016/j.cma.2022.114909
References
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