Connections between deep learning and partial differential equations

DOI10.1017/S0956792521000085zbMath1479.35002OpenAlexW3157498305WikidataQ115335728 ScholiaQ115335728MaRDI QIDQ5014844

Martin Burger, Lars Ruthotto, E. Weinan, Stanley J. Osher

Publication date: 8 December 2021

Published in: European Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s0956792521000085

zbMATH Keywords

linearising nonlinear PDEs through coordinate transformations

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Transform methods (e.g., integral transforms) applied to PDEs (35A22) Nonlinear higher-order PDEs (35G20) Theoretical approximation in context of PDEs (35A35) Research exposition (monographs, survey articles) pertaining to partial differential equations (35-02)

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Cites Work

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