Mean-field neural networks: Learning mappings on Wasserstein space-Reference-Cited by-同舟云学术

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Mean-field neural networks: Learning mappings on Wasserstein space

Published:2023-11 Issue: Volume:168 Page:380-393
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Pham Huyên^ORCID,Warin Xavier^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference25 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous systems;Abadi,2015

2. An overview on deep learning-based approximation methods for PDEs;Beck;Discrete and Continuous Dynamical Systems,2023

3. Notes on mean field games;Cardaliaguet,2013

4. Probabilistic theory of mean field games: Vol. I, mean field FBSDEs, control, and games;Carmona,2018

5. Probabilistic theory of mean field games: Vol. II, mean field FBSDEs, control, and games;Carmona,2018

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On Lipschitz solutions of mean field games master equations;Journal of Functional Analysis;2024-09

2. Time-Varying Function Matrix Projection Synchronization of Caputo Fractional-Order Uncertain Memristive Neural Networks with Multiple Delays via Mixed Open Loop Feedback Control and Impulsive Control;Fractal and Fractional;2024-05-20

3. Optimal Control of Nonlocal Continuity Equations: Numerical Solution;Applied Mathematics & Optimization;2023-10-05

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