PyTorch Implementation for Gromov-Wasserstein Autoencoders (GWAE)

Predict the binding affinity of protein-protein complexes from structural data

Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.

Generative Language Modeling for Antibody Design

User friendly and accurate binder design pipeline

TorchDR - PyTorch Dimensionality Reduction

Open source implementation of AlphaFold3

Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold

PINDER: The Protein INteraction Dataset and Evaluation Resource

Minimalist implementation of VQ-VAE in Pytorch

A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

Learning meaningful representations of genes

Learning meaningful representations of genes

Diffusion-based all-atom protein generative model.

[ICLR 2024 Spotlight] The official repo for the paper "De novo Protein Design using Geometric Vector Field Networks".

This repository implements variational graph auto encoder by Thomas Kipf.

A minimal helper for ploting 3D scatter plots with plotly

Transformer Based Embeddings of Wasserstein Distance

In-silico design pipeline for evaluating protein structure diffusion models.

Repo for "Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture"

Lbster: Language models for Biological Sequence Transformation and Evolutionary Representation

Code for “FlowMM Generating Materials with Riemannian Flow Matching”.

ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

A fast multiple sequence alignment program.

An Extensible Deep Learning Library