Y-H-Joe

Y-H-Joe's Stars

• evolutionaryscale/esm

  Language:Python1.2k131

• drorlab/gvp

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

  Language:Python12933

• A4Bio/ProteinInvBench

  The official implementation of the NeurIPS'23 paper ProteinInvBench: Benchmarking Protein Design on Diverse Tasks, Models, and Metrics

  Language:Python1616

• files-community/Files

  Building the best file manager for Windows

  Language:C#34.1k2.2k

• Ecogenomics/GTDBTk

  GTDB-Tk: a toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.

  Language:Python47082

• steineggerlab/foldseek

  Foldseek enables fast and sensitive comparisons of large structure sets.

  Language:C78199

• deepmodeling/deepmd-kit

  A deep learning package for many-body potential energy representation and molecular dynamics

  Language:C++1.5k504

• deepmodeling/DMFF

  DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable implementation of molecular force field models.

  Language:Python15143

• deepmodeling/Uni-Mol

  Official Repository for the Uni-Mol Series Methods

  Language:Python677119

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.3k6.4k

• lsj2408/Transformer-M

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

  Language:Python20024

• Y-H-Joe/Y-H-Joe.github.io

  Language:HTML1

• Y-H-Joe/OUTPOST

  Language:HTML51

• DeepGraphLearning/GearNet

  GearNet and Geometric Pretraining Methods for Protein Structure Representation Learning, ICLR'2023 (https://arxiv.org/abs/2203.06125)

  Language:Python26427

• microsoft/AI2BMD

  AI-powered ab initio biomolecular dynamics simulation

  Language:Python17419

• microsoft/Graphormer

  Graphormer is a general-purpose deep learning backbone for molecular modeling.

  Language:Python2.1k334

• datawhalechina/easy-rl

  强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

  Language:Jupyter Notebook9.2k1.8k

• wengong-jin/RefineGNN

  Language:Python12723

• lrjconan/GRAN

  Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

  Language:C++46597

• dengjianyuan/Survey_AI_Drug_Discovery

  30664

• yangkky/Machine-learning-for-proteins

  Listing of papers about machine learning for proteins.

  1.5k198

• facebookresearch/esm

  Evolutionary Scale Modeling (esm): Pretrained language models for proteins

  Language:Python3.2k627

• idlutz/protein-backbone-MCTS

  Language:Python467

• RosettaCommons/RFdiffusion

  Code for running RFdiffusion

  Language:Python1.7k325

• huawei-noah/HEBO

  Bayesian optimisation & Reinforcement Learning library developped by Huawei Noah's Ark Lab

  Language:Jupyter Notebook3.2k585

• csi-greifflab/Absolut

  Unconstrained lattice antibody-antigen bindings generator

  Language:Jupyter Notebook9818

• Peldom/papers_for_protein_design_using_DL

  List of papers about Proteins Design using Deep Learning

  1.4k171

• pyro-ppl/pyro

  Deep universal probabilistic programming with Python and PyTorch

  Language:Python8.5k984

• jalammar/ecco

  Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).

  Language:Jupyter Notebook2k167

• jessevig/bertviz

  BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

  Language:Python6.8k773