Port-Hamiltonian neural networks for learning explicit time-dependent dynamical systems
Accurately learning the temporal behavior of dynamical systems requires models with well-chosen learning biases. Recent innovations embed the Hamiltonian and Lagrangian formalisms into neural networks and demonstrate a significant improvement over other approaches in predicting trajectories of physi...
| Үндсэн зохиолчид: | , , , , |
|---|---|
| Формат: | Journal article |
| Хэл сонгох: | English |
| Хэвлэсэн: |
American Physical Society
2021
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