Deep splitting method for parabolic PDEs
In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational graph for each of the subproblems is comparatively small,...
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| Main Authors: | , , , , |
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| 其他作者: | |
| 格式: | Article |
| 語言: | English |
| 出版: |
2022
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/153744 |
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