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MACE                       🚀 JAX

This repository contains a porting of MACE in jax developed by Mario Geiger and Ilyes Batatia.

Test without installing

pip install nox
nox

Installation

From github:

pip install git+https://github.com/ACEsuit/mace-jax

Or locally:

python setup.py develop

Usage

Training

To train a MACE model, you can use the run_train.py script:

python -m mace_jax.run_train config.gin

An example of configuration file is located in the directory configs.

Configuration

Links to the files containing the functions configured by the gin config file.

Contributions

We are happy to accept pull requests under an MIT license. Please copy/paste the license text as a comment into your pull request.

References

If you use this code, please cite our papers:

@misc{Batatia2022MACE,
  title = {MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields},
  author = {Batatia, Ilyes and Kov{\'a}cs, D{\'a}vid P{\'e}ter and Simm, Gregor N. C. and Ortner, Christoph and Cs{\'a}nyi, G{\'a}bor},
  year = {2022},
  number = {arXiv:2206.07697},
  eprint = {2206.07697},
  eprinttype = {arxiv},
  doi = {10.48550/ARXIV.2206.07697},
  archiveprefix = {arXiv}
}
@misc{Batatia2022Design,
  title = {The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials},
  author = {Batatia, Ilyes and Batzner, Simon and Kov{\'a}cs, D{\'a}vid P{\'e}ter and Musaelian, Albert and Simm, Gregor N. C. and Drautz, Ralf and Ortner, Christoph and Kozinsky, Boris and Cs{\'a}nyi, G{\'a}bor},
  year = {2022},
  number = {arXiv:2205.06643},
  eprint = {2205.06643},
  eprinttype = {arxiv},
  doi = {10.48550/arXiv.2205.06643},
  archiveprefix = {arXiv}
 }

Contact

If you have any questions, please contact us at [email protected] or [email protected].

License

MACE is published and distributed under the MIT.