[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

MatTen: Equivariant Graph Neural Nets for Tensorial Properties of Materials

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

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

Implementation of the Confidence Bootstrapping procedure for protein-ligand docking.

Deep Learning Potential model with Symmetry Invariant and Equivariant Descriptor

TESGNN: 3D Temporal Equivariant Scene Graph Neural Networks

E(3)-Equivariant Mesh Neural Networks (AISTATS 2024)

Rotationally Equivariant Hypergraph Neural Networks (EquiHGNN)

Employing Molecular Conformations for Ligand-based Virtual Screening with Equivariant Graph Neural Network and Deep Multiple Instance Learning

OM-Diff: Inverse-design of organometallic catalysts with guided equivariant denoising diffusion

This repository provides implementations for sparse graph separation, power graph experiments, and chemical property prediction.

Implementation of Geometrically Equivariant Graph Neural Networks (GNNs) in PyTorch.

Implementation in Pytorch of the article "E(n) Equivariant Graph Neural Network" - Satorras et al.