Learning unbounded-domain spatiotemporal differential equations using adaptive spectral methods
Rapidly developing machine learning methods have stimulated research interest in computationally reconstructing differential equations (DEs) from observational data, providing insight into the underlying mechanistic models. In this paper, we propose a new neural-ODE-based method that spectrally expa...
| Principais autores: | , , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
Springer
2024
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