Open-source alternatives to Schnetpack

MatGL (Materials Graph Library) is a graph deep learning library for materials science. Mathematical graphs are a natural representation for a collection of atoms. Graph deep learning models have been shown to consistently deliver exceptional performance as surrogate models for the prediction of…

Universal Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structures

Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki, Naoya Chiba, Kotaro Saito, Yoshitaka Ushiku, and Kanta Ono In The Twelfth International Conference on Learning Representations (ICLR 2024)

Rethinking the role of frames for SE(3)-invariant crystal structure modeling Yusei Ito, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku, and Kanta Ono In The Thirteenth International Conference on Learning Representations (ICLR 2025)

AdsorbML is an algorithm to calculating the minima adsorbate binding energy (adsorption energy) for a unique adsorbate+surface combination. All ML models are obtained from ocp to perform corresponding structure relaxations.

The Compositionally-Restricted Attention-Based Network (CrabNet), inspired by natural language processing transformers, uses compositional information to predict material properties.

This software package implements our developed model GATGNN for improved inorganic materials' property prediction. This is the official Pytorch repository.

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