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Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction

The implementation of Xtal2DoS using PyTorch.

Sample Dataset

Datasets can be found here.

Environment

Run ./install.sh

Dependencies

  • Python 3.10.4
  • PyTorch 1.11.0
  • numpy 1.22.4
  • sklearn 1.1.1
  • cuda 11.3

Older versions might work as well.

Run

To train the model: bash scrips/run_train.sh

To test the model: bash scripts/run_test.sh

Paper

If you find our work inspiring, please consider citing the following paper:

@inproceedings{bai2022xtaldos,
  title={Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction},
  author={Junwen Bai and Yuanqi Du and Yingheng Wang and Shufeng Kong and John Gregoire and Carla P Gomes},
  booktitle={NeurIPS 2022 AI for Science: Progress and Promises},
  year={2022}
}