PET

This repository contains an implementation of Point Edge Transformer (PET), interatomic machine learning potential, which achieves state-of-the-art on several datasets; see more details in [1]. PET is a graph neural network where each message-passing layer is given by an arbitrarily deep transformer. Additionally, this repository contains a proof-of-principle implementation of the Equivariant Coordinate System Ensemble (ECSE).

Installation

Run pip install .

After the installation, the following command line scripts are available: pet_train, pet_run, and pet_run_sp.

See the documentation for more details.

Train model

• Train model

Hyperparameters selection

• Select hyperparameters

Run model

• Run model

References

[1] Sergey Pozdnyakov, and Michele Ceriotti 2023. Smooth, exact rotational symmetrization for deep learning on point clouds. In Thirty-seventh Conference on Neural Information Processing Systems.