Joint embedding of protein sequence and structure with discrete and continuous compressions of protein folding model latent spaces. https://www.biorxiv.org/content/10.1101/2024.08.06.606920v1

A generative model for programmable protein design

Google Drive CLI Client

Q&A, homeworks, etc.

Tool for deep mutational scanning experiments.

Official code repository for the paper "ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers"

official Pytorch implementation of ICCV 2021 paper FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting.

[ECCV'2020] STTN: Learning Joint Spatial-Temporal Transformations for Video Inpainting

Sandbox for Deep-Learning based Computational Protein Design

Generation of protein sequences and evolutionary alignments via discrete diffusion models

Repository for code and models for the paper "Extrapolative Controlled Sequence Generation via Iterative Refinement"

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Traffic Prediction models - UAGCRN and UAGCTransformer

This repository implements Gibbs sampling with Graph-based Smoothing

Reference implementation for DPO (Direct Preference Optimization)

Implementation of Tranception, an attention network, paired with retrieval, that is SOTA for protein fitness prediction

Unofficial implementation of Palette: Image-to-Image Diffusion Models by Pytorch

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

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

A lightning-fast search API that fits effortlessly into your apps, websites, and workflow

Personal Webpage

Source code for Twitter's Recommendation Algorithm

Official repository for the paper "Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval"

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

[ICLR 2023] "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules"

Implementation and experiments of graph embedding algorithms.

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities