ayz2/hamiltonian_pdes
Hamiltonian Neural PDE Solvers through Functional Approximation (NeurIPS 2025) 1D Datasets 1D data is generated for the 1D Advection and 1D KdV equations, from Masked Autoencoder are PDE Learners and Lie Point Symmetry Data Augmentation for Neural PDE Solvers. Adv datasets have a resolution of 128, with 200 timesteps for train and 1000 timesteps for validation. KdV datasets have a resolution of 256, with 200 timesteps for train and 200 timesteps for validation… See the full description on the dataset page: https://huggingface.co/datasets/ayz2/hamiltonian_pdes.
| Author / organization | ayz2 |
|---|---|
| License (as declared) | mit |
| Downloads | 163 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 16 May 2025 |
| Last updated at source | 30 September 2025 |
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- 16 Oct 2026 Description: Hamiltonian Neural PDE Solvers through Functional Approximation (NeurIPS 2025) 1D Datasets 1D data is generated for the 1D Advection and 1D KdV equations, from Masked Autoencoder are PDE Learners and Lie Point Symmetry Data Augmentation for → Hamiltonian Neural PDE Solvers through Functional Approximation (NeurIPS 2025) 1D Datasets 1D data is generated for the 1D Advection and 1D KdV equations, from Masked Autoencoder are PDE Learners and Lie Point Symmetry Data Augmentation for
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