Monte Carlo Neural PDE Solver for Learning PDEs Via Probabilistic Representation
In scenarios with limited available data, training the function-to-function neural PDE solver in an unsupervised manner is essential. However, the efficiency and accuracy of existing methods are constrained by the properties of numerical algorithms, such as finite difference and pseudo-spectral meth...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2025) vom: 07. März
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| 1. Verfasser: |
Zhang, Rui
(VerfasserIn) |
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| Weitere Verfasser: |
Meng, Qi,
Zhu, Rongchan,
Wang, Yue,
Shi, Wenlei,
Zhang, Shihua,
Ma, Zhi-Ming,
Liu, Tie-Yan |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2025
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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