[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 J2C Certification] 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.

TESGNN: 3D Temporal Equivariant Scene Graph Neural Networks (published at TMLR)

Rotationally Equivariant Hypergraph Neural Networks (EquiHGNN)

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

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

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

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

A mathematical/computational framework that upgrades the complex numbers for working with unified 2D coordinates, inversive geometry, Eisenstein integers, radial dual triangular lattice graph (RDTLG), hexagonal symmetries, signal processing, equivariant encodings, and geometric deep learning.

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

Using high-throughput DFT, Wannier90, and TB2J, this project calculates the magnetic exchange interactions of 2D CrI3 under mechanical strain to reveal how structural distortions modulate its Heisenberg parameters.

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