Galerkin Neural Networks: A Framework for Approximating Variational Equations with Error Control-Reference-Cited by-同舟云学术

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Galerkin Neural Networks: A Framework for Approximating Variational Equations with Error Control

Published:2021-01 Issue:4 Volume:43 Page:A2474-A2501
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Ainsworth Mark,Dong Justin

Funder

PhILMS

National Science Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Computational Mathematics

Link

https://epubs.siam.org/doi/pdf/10.1137/20M1366587

Reference16 articles.

1. A unified deep artificial neural network approach to partial differential equations in complex geometries

2. Approximation by superpositions of a sigmoidal function

3. Neural-network-based approximations for solving partial differential equations

4. Solving high-dimensional partial differential equations using deep learning

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