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Tim.S's Projects

18s191 icon 18s191

Course 18.S191 at MIT, Spring 2021 - Introduction to computational thinking with Julia:

alphafold2-lucidrains icon alphafold2-lucidrains

To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released

alphalink icon alphalink

AlphaLink: Integrating crosslinking-MS data into OpenFold

chatlm-mini-chinese icon chatlm-mini-chinese

中文对话0.2B小模型(ChatLM-Chinese-0.2B),开源所有数据集来源、数据清洗、tokenizer训练、模型预训练、SFT指令微调、RLHF优化等流程的全部代码。支持下游任务sft微调,给出三元组信息抽取微调示例。

coati icon coati

COATI: multi-modal contrastive pre-training for representing and traversing chemical space

convnetjs icon convnetjs

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

ddpm-proteins icon ddpm-proteins

A denoising diffusion probabilistic model (DDPM) tailored for conditional generation of protein distograms

deeprank-gnn-esm icon deeprank-gnn-esm

Graph Network for protein-protein interface including language model features

det3d icon det3d

A general 3D object detection codebse.

diffdock icon diffdock

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

difflinker icon difflinker

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

diffsbdd icon diffsbdd

A Euclidean diffusion model for structure-based drug design.

dynamicbind icon dynamicbind

repo for DynamicBind: Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model

egnn-pytorch icon egnn-pytorch

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

en-transformer icon en-transformer

Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention

evodiff icon evodiff

Generation of protein sequences and evolutionary alignments via discrete diffusion models

geodock icon geodock

Flexible Protein-Protein Docking with a Multi-Track Iterative Transformer.

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