Parameter/topology editor and molecular simulator

Hierarchical Generation of Molecular Graphs using Structural Motifs

Implementation for SE(3) diffusion model with application to protein backbone generation

Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks, CVPR 2020

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

Graph neural networks for molecular design.

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

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

✌🏻 Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures (NeurIPS 2022)

Our own implementation of Neural Message Passing for Computer Vision paper

Deep functional residue identification

OctFormer: Octree-based Transformers for 3D Point Clouds [SIGGRAPH 2023]

The code of a graph neural network (GNN) for molecules, which is based on learning representations of r-radius subgraphs (i.e., fingerprints) in molecules.

A Graph Attention Spatio-temporal Convolutional Networks for 3D Human Pose Estimation in Video (GAST-Net)

Interface for AutoDock, molecule parameterization

Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

Simple implementation of mean shift clustering in python

Mol2vec - an unsupervised machine learning approach to learn vector representations of molecular substructures

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

Implementation of the Paper "Learning Continuous and Data-Driven Molecular Descriptors by Translating Equivalent Chemical Representations" by Robin Winter, Floriane Montanari, Frank Noe and Djork-A…

Ankh: Optimized Protein Language Model

Deep generative models of 3D grids for structure-based drug discovery

BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis

ChEMBL database structure pipelines

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

[ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)

Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology

💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)