A Descent Algorithm for the Optimal Control of ReLU Neural Network Informed PDEs Based on Approximate Directional Derivatives-Reference-Cited by-同舟云学术

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A Descent Algorithm for the Optimal Control of ReLU Neural Network Informed PDEs Based on Approximate Directional Derivatives

Published:2024-07-02 Issue:3 Volume:34 Page:2314-2349
ISSN:1052-6234
Container-title:SIAM Journal on Optimization
language:en
Short-container-title:SIAM J. Optim.

Author:

Dong Guozhi¹^ORCID,Hintermüller Michael²^ORCID,Papafitsoros Kostas³^ORCID

Affiliation:

1. School of Mathematics and Statistics, HNP-LAMA, Central South University, 410083, Changsha, China.

2. Institute for Mathematics, Humboldt-Universität zu Berlin, 10099, Berlin, Germany, and Weierstrass Institute for Applied Analysis and Stochastics (WIAS), 10117, Berlin, Germany.

3. School of Mathematical Sciences, Queen Mary University of London, E1 4NS, UK.

Funder

Deutsche Forschungsgemeinschaft

National Natural Science Foundation of China

Innovative Platform Project of Hunan Province

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference25 articles.

1. Learning-Informed Parameter Identification in Nonlinear Time-Dependent PDEs

2. CONTINUOUS PIECEWISE LINEAR FUNCTIONS

3. Set-Valued Analysis

4. Res. Notes Math. 100;Barbu V.,1984

5. Representation Learning: A Review and New Perspectives

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