GeoPT/Downstream_Physics_Simulation
GeoPT Project Page | Paper | GitHub This repository contains the physics simulation data for the paper GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training. GeoPT is a unified model pre-trained on large-scale geometric data for general physics simulation, unlocking a scalable path for neural simulation. Overview GeoPT is evaluated on the following five simulation tasks. Dataset Mesh Size Variable Training Test Total Size Source… See the full description on the dataset page: https://huggingface.co/datasets/GeoPT/Downstream_Physics_Simulation.
GeoPT
Project Page | Paper | GitHub
This repository contains the physics simulation data for the paper GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training.
GeoPT is a unified model pre-trained on large-scale geometric data for general physics simulation, unlocking a scalable path for neural simulation.
<p align="center"> <img src="assets/GeoPT.png" height = "120" alt="" align=center /> </p>
Overview
GeoPT is evaluated on the following five simulation tasks.
Load Data
from datasets import load_dataset
# For AirCraft, DTCHull, Car-Crash
load_dataset("GeoPT/Downstream_Physics_Simulation")
# For DrivAerML
load_dataset("neashton/drivaerml") NASA-CRM can be obtained from Google Drive.
Examples
<p align="center"> <img src="assets/examples.png" height = "140" alt="" align=center /> </p>
Citation
If you find this repo useful, please cite our paper.
@article{wu2026GeoPT,
title={GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training},
author={Haixu Wu, Minghao Guo, Zongyi Li, Zhiyang Dou, Mingsheng Long, Kaiming He, Wojciech Matusik},
booktitle={arXiv preprint arXiv:2602.20399},
year={2026}
}Contact
If you have any questions or want to use the code, please contact Haixu Wu (wuhaixu98@gmail.com) and Minghao Guo (guomh2014@gmail.com).