rociomer

fairseq

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

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

taming-transformers

Taming Transformers for High-Resolution Image Synthesis

DALLE-pytorch

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

machine-learning-book

Code Repository for Machine Learning with PyTorch and Scikit-Learn

neural-processes

This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).

ProteinMPNN

Code for the ProteinMPNN paper

practical_cheminformatics_tutorials

Practical Cheminformatics Tutorials

ganttrify

Create beautiful Gantt charts with ggplot2

dmol-book

Deep learning for molecules and materials book

tokengt

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

folding_tools

A collection of *fold* tools

molecule-generation

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

torsional-diffusion

Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)

espsim

Scoring of shape and ESP similarity with RDKit

mol_opt

CHEM101.6

Smiles-TO-iUpac-Translator

Transformer based SMILES to IUPAC Translator

pre-training-via-denoising

Official implementation of pre-training via denoising for TorchMD-NET

GB_GA

Graph-based genetic algorithm

OChemR

From a chemical reaction image, detect and classify molecules, text and arrows by using the Vision Transformer DETR. Comparisons with well-established CNNs (RetinaNet and FasterRCNN also provided). The detections are then translated into text "OCR" or into SMILES. The direction of the reaction is learned and preserved into the output files.

UGM_2022

Materials from the 2022 UGM

cookiecutter-snekpack

🍪 A cookiecutter package for an enlightened python package

Protac-Design

UROP Project @ Coley Group

WS-DINO

WS-DINO: a novel framework to use weak label information in a self-supervised setting to learn phenotypic representations from high-content fluorescent images of cells.

QM-augmented_GNN

MolKGNN

MolKGNN is a deep learning model for predicting biological activity or molecular properties. It features in 1. SE(3)-invariance 2. conformation-invariance 3. interpretability. MolKGNN uses a novel molecular convolution to leverage the similarity of molecular neighborhood and kernels. It shows superior results in realistic drug discovery datasets.

NiCOlit

Repository for the featurization of the NiCOlit reaction dataset and machine learning model training for yield prediction

SynNet