deepmind-research/learning_to_simulate

Learning to Simulate Complex Physics with Graph Networks

This is a model implementation for the ICML 2020 submission (also available in arXiv arxiv.org/abs/2002.09405. If you use the code here please cite this paper:

@article{sanchezgonzalez2020learning,
    title={Learning to Simulate Complex Physics with Graph Networks},
    author={Alvaro Sanchez-Gonzalez and
            Jonathan Godwin and
            Tobias Pfaff and
            Rex Ying and
            Jure Leskovec and
            Peter W. Battaglia},
    url={https://arxiv.org/abs/2002.09405},
    year={2020},
    eprint={2002.09405},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

Contents

• model.py: implementation of the graph network use as the learnable part of the model.
• model_demo.py: example connecting the model to input dummy data.

Running demo

(From one directory above)

pip install -r learning_to_simulate/requirements.txt
python -m learning_to_simulate.model_demo