Popular GitHub Repositories for Materials Science

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

A deep learning package for many-body potential energy representation and molecular dynamics

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

MatterSim: A deep learning atomistic model across elements, temperatures and pressures.

Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.

Crystal Graph Neural Networks

MACE-MP models

Unsupervised learning of atomic scale dynamics from molecular dynamics.

Public release of data and code for materials synthesis generation

How good are LLMs at chemistry?

Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.

Graph-Aware Attention for Adaptive Dynamics in Transformers

Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."

Evaluation of universal machine learning force-fields https://arxiv.org/abs/2412.10516

A flexible and performant framework for training machine learning potentials.

CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)

The official code respository for "Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding" (ICLR 2024)

Probabilistic machine learning for reconstruction and parametrization of electronic band sturcture from photoemission spectroscopy data

Computational analysis of nucleic acids structures using graph neural networks

Official implementation of "Gradient Boosted and Statistical Feature Selection Pipeline for Materials Property Predictions"