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NN-Poly: Approximating common neural networks with Taylor polynomials to imbue dynamical system constraints
Recent advances in deep learning have bolstered our ability to forecast the evolution of dynamical systems, but common neural networks do not adhere to physical laws, critical information that could lead to sounder state predictions. This contribution addresses this concern by proposing a neural net...
Autores principales: | Zhu, Frances, Jing, Dongheng, Leve, Frederick, Ferrari, Silvia |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680843/ https://www.ncbi.nlm.nih.gov/pubmed/36425848 http://dx.doi.org/10.3389/frobt.2022.968305 |
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