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Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach
The issue of the relaxation to equilibrium has been at the core of the kinetic theory of rarefied gas dynamics. In the paper, we introduce the Deep Neural Network (DNN) approximated solutions to the kinetic Fokker-Planck equation in a bounded interval and study the large-time asymptotic behavior of...
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| 出版年: | J Comput Phys |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Elsevier Inc.
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7286285/ https://ncbi.nlm.nih.gov/pubmed/32834105 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jcp.2020.109665 |
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