DreRnc

context-guided-diffusion

Code for the paper Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design

JMP

Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.

Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.

awesome-scalability

The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

useful_rdkit_utils

Some useful RDKit functions

pinder

PINDER: The Protein INteraction Dataset and Evaluation Resource

plinder

Protein Ligand INteraction Dataset and Evaluation Resource

confidence-bootstrapping

Implementation of the Confidence Bootstrapping procedure for protein-ligand docking.

Uni-Mol

Official Repository for the Uni-Mol Series Methods

disco-diffdock

Code for the paper DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents, ICML 2024

DiffDock

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

Awesome-Graph-Research-ICML2024

All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.

AkomaNtosoBulkData

Bulk data dei documenti legislativi in formato Akoma Ntoso

misato-dataset

openfold

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

esm

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

mamba

Mamba SSM architecture

awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

egnn-pytorch

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

pna

Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric

gvp-pytorch

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

python-whatsapp-bot

Build AI WhatsApp Bots with Pure Python

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

denoising-diffusion-pytorch

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

LightGBM

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

gpt-fast

Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

minGPT

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

clifford-group-equivariant-neural-networks

Code used by the "Clifford Group Equivariant Neural Networks" paper.