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Lie Group Cohomology and (Multi)Symplectic Integrators: New Geometric Tools for Lie Group Machine Learning Based on Souriau Geometric Statistical Mechanics
In this paper, we describe and exploit a geometric framework for Gibbs probability densities and the associated concepts in statistical mechanics, which unifies several earlier works on the subject, including Souriau’s symplectic model of statistical mechanics, its polysymplectic extension, Koszul m...
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| 出版年: | Entropy (Basel) |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7516986/ https://ncbi.nlm.nih.gov/pubmed/33286271 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22050498 |
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