Popular GitHub Repositories for Computational Chemistry

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

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

一种用于三维分子生成和优化的几何完备扩散生成模型（发表于《自然-通讯化学》）

A collection of Nerual Network Models for chemistry

Mixed continous/categorical flow-matching model for de novo molecule generation.

一种用于生成性蛋白质-配体对接和亲和力预测的几何流匹配模型（ISMB 2025）

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

Code for our Nature Scientific Reports paper "A universal framework for accurate and efficient geometric deep learning of molecular systems"

Quantum computational chemistry based on TensorCircuit

Sample-based Quantum Diagonalization: Classically postprocess noisy quantum samples to yield more accurate eigenvalue estimations.

Graph neural networks for molecular machine learning. Implemented and compatible with TensorFlow and Keras.

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)

[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields

Graph-based machine learning for chemical property prediction

A flexible and performant framework for training machine learning potentials.

Reproduction of CGCNN with fine-tuning for predicting material properties

Quantum computational chemistry based on TensorCircuit

Master thesis: JAT (Jraph Attention Networks), a deep learning architecture to predict the potential energy and forces of molecules. Adapts Graph Attention Networks (GATv2) within the Message Passing Neural Networks framework to computational chemistry in JAX

Activation energy prediction from SMILES strings