| datasets: | |
| - scailab/hyper-navier-stokes-64-1000 | |
| language: | |
| - en | |
| library_name: pytorch | |
| pipeline_tag: time-series-forecasting | |
| # HyPER Model Checkpoints | |
| We provide pytorch model checkpoints for the ICML 2025 paper **Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout** ([https://huggingface.co/papers/2503.10048](https://huggingface.co/papers/2503.10048)). | |
| Please see https://github.com/scailab/HyPER for our code and instructions to train and evaluate these models. |