Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

A Euclidean diffusion model for structure-based drug design.

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

E(2)-Equivariant CNNs Library for Pytorch

Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/

DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)

Implementation of E(n)-Transformer, which incorporates attention mechanisms into Welling's E(n)-Equivariant Graph Neural Network

Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold for protein folding

Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. This specific repository is geared towards integration with eventual Alphafold2 replication.

A Local Frame-based Atomistic Potential

Multi-domain Distribution Learning for De Novo Drug Design

Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023

A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

[NAACL 2022] Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning.

Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch

[NeurIPS'21] Higher-order Transformers for sets, graphs, and hypergraphs, in PyTorch