| license: mit | |
| task_categories: | |
| - time-series-forecasting | |
| tags: | |
| - physics | |
| - PDE | |
| - scientific-computing | |
| - neural-operators | |
| - zebra | |
| - enma | |
| # 2D Wave Equation Dataset | |
| 2d wave equation dataset. The underlying PDE is the **wave equation**. | |
| Data is stored in HDF5 (`.h5`) format. | |
| ## Origin | |
| This dataset was generated by **Armand Kassai Koupaï** and has been used in the following papers: | |
| - **ZEBRA: In-Context Generative Pretraining for Solving Parametric PDEs** — Louis Serrano, Armand Kassaï Koupaï, Thomas X Wang, Pierre Erbacher, Patrick Gallinari. *ICML 2025*. [OpenReview](https://openreview.net/forum?id=22kNOkkokU) | |
| - **ENMA: Tokenwise Autoregression for Generative Neural PDE Operators** — Armand Kassaï Koupaï, Lise Le Boudec, Louis Serrano, Patrick Gallinari. *NeurIPS 2025*. | |
| ## Download | |
| See the full download script in the [Zebra repository](https://github.com/LouisSerrano/zebra). | |
| ```bash | |
| pip install huggingface_hub | |
| python download_data/download_data_hugging_face.py --datasets wave | |
| ``` | |
| ## Usage | |
| ```python | |
| import h5py | |
| data = h5py.File("train.h5", "r") | |
| ``` | |