{"id":15118995,"url":"https://github.com/Bayer-Group/eqgat","last_synced_at":"2025-09-28T01:31:37.458Z","repository":{"id":89208625,"uuid":"571741079","full_name":"Bayer-Group/eqgat","owner":"Bayer-Group","description":"Research repository for the proposed equivariant graph attention network that operates on large biomolecules proposed by Le et al. 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Additionally, we provide implementations of other recent 3D Graph Neural Networks.\n* `experiments/` contains the 5 python training-scripts from the [ATOM3D](https://www.atom3d.ai/) and 1 synthetic datasets. To execute each training script, please refer to the corresponding README.md in the sub-directories. \n\n### Installation with GPU support\n```\n# install the conda environment\nconda env create -f environment.yml \nconda activate eqgat\npip install -e .\n```\n\n### Experiments\nAll experiments presented in the paper can be found in the `experiments/` directory.  \nMake sure to download all requested public datasets from [ATOM3D](https://www.atom3d.ai/) as described in the corresponding READMEs.\n\n\n### Example \nA minimal example using the proposed SO(3) equivariant graph attention network can be found in `eqgat/README.md`\n\n### License\nCode is available under BSD 3-Clause License.\n\n### Reference\nIf you make use of our model architecture, please cite our full-length manuscript:\n\u003eT. Le et al., Representation Learning on Biomolecular Structures using Equivariant Graph Attention. *Proceedings\nof the First Learning on Graphs Conference (LoG 2022)*, PMLR 198, Virtual Event, December 9–12, 2022.\n\n```\n@inproceedings{\nle2022representation,\ntitle={Representation Learning on Biomolecular Structures using Equivariant Graph Attention},\nauthor={Tuan Le and Frank Noe and Djork-Arn{\\'e} Clevert},\nbooktitle={Learning on Graphs Conference},\nyear={2022},\nurl={https://openreview.net/forum?id=kv4xUo5Pu6}\n}\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FBayer-Group%2Feqgat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FBayer-Group%2Feqgat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FBayer-Group%2Feqgat/lists"}