VPNets: Volume-preserving neural networks for learning source-free dynamics-Reference-Cited by-同舟云学术

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VPNets: Volume-preserving neural networks for learning source-free dynamics

Published:2022-12 Issue: Volume:416 Page:114523
ISSN:0377-0427
Container-title:Journal of Computational and Applied Mathematics
language:en
Short-container-title:Journal of Computational and Applied Mathematics

Author:

Zhu Aiqing^ORCID,Zhu Beibei^ORCID,Zhang Jiawei,Tang Yifa,Liu Jian

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference46 articles.

1. Automated reverse engineering of nonlinear dynamical systems;Bongard;Proc. Natl. Acad. Sci.,2007

2. Distilling free-form natural laws from experimental data;Schmidt;Science,2009

3. Machine learning of linear differential equations using Gaussian processes;Raissi;J. Comput. Phys.,2017

4. Dynamic systems identification with Gaussian processes;Kocijan;Math. Comput. Model. Dyn. Syst.,2005

5. Chaos as an intermittently forced linear system;Brunton;Nature Commun.,2017

Cited by 1 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. Forty years: Geometric numerical integration of dynamical systems in China;International Journal of Modeling, Simulation, and Scientific Computing;2024-08-28

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