Energetic Variational Neural Network Discretizations of Gradient Flows-Reference-Cited by-同舟云学术

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Energetic Variational Neural Network Discretizations of Gradient Flows

Published:2024-08-05 Issue:4 Volume:46 Page:A2528-A2556
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Hu Ziqing¹,Liu Chun²,Wang Yiwei³,Xu Zhiliang¹

Affiliation:

1. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN 46556, USA.

2. Department of Applied Mathematics, Illinois Institute of Technology, Chicago, IL 60616, USA.

3. Corresponding author. Department of Mathematics, University of California, Riverside, Riverside, CA 92521, USA.

Funder

National Science Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference63 articles.

1. Large deviations and gradient flows

2. Universal approximation bounds for superpositions of a sigmoidal function

3. A computational fluid mechanics solution to the Monge-Kantorovich mass transfer problem

4. An augmented Lagrangian approach to Wasserstein gradient flows and applications

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