https://hanjq17.github.io/SGNN/
[NeurIPS 2022] The implementation for the paper "Learning Physical Dynamics with Subequivariant Graph Neural Networks".
https://hanjq17.github.io/SGNN/
graph-neural-networks physical-simulation symmetry
Last synced: 10 months ago
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[NeurIPS 2022] The implementation for the paper "Learning Physical Dynamics with Subequivariant Graph Neural Networks".
- Host: GitHub
- URL: https://hanjq17.github.io/SGNN/
- Owner: hanjq17
- License: mit
- Created: 2022-10-10T05:58:51.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-11-01T18:17:14.000Z (over 3 years ago)
- Last Synced: 2023-03-11T20:34:48.205Z (over 3 years ago)
- Topics: graph-neural-networks, physical-simulation, symmetry
- Language: Python
- Homepage: https://arxiv.org/pdf/2210.06876.pdf
- Size: 11.4 MB
- Stars: 9
- Watchers: 2
- Forks: 0
- Open Issues: 0