rociomer

PlotNeuralNet

Latex code for making neural networks diagrams

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

NN-SVG

Publication-ready NN-architecture schematics.

awesome-network-embedding

A curated list of network embedding techniques.

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

Graphormer

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

awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

HowToTrainYourMAMLPytorch

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

chemicalx

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

maml_rl

Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

hypergrad

Exploring differentiation with respect to hyperparameters

leo

Implementation of Meta-Learning with Latent Embedding Optimization

exmol

Explainer for black box models that predict molecule properties

molplotly

add-on to plotly which show molecule images on mouseover!

jax2torch

Use Jax functions in Pytorch

awesome-drug-discovery-knowledge-graphs

A collection of research papers, datasets and software related to knowledge graphs for drug discovery. Accompanies the paper "A review of biomedical datasets relating to drug discovery: a knowledge graph perspective" (Briefings in Bioinformatics, 2022)

MatDeepLearn

MatDeepLearn, package for graph neural networks in materials chemistry

FS-Mol

FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

3DInfomax

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

dockstring

A Python package for molecular docking with an extensive, highly-curated dataset and a set of realistic benchmark tasks for drug discovery.

GraphiT

Official Pytorch Implementation of GraphiT

PaRoutes

Home of the PaRoutes framework for benchmarking multi-step retrosynthesis predictions.

ChIRo

Public Implementation of ChIRo from "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"

caviar

// PROJECT PAUSED FOR NOW (lack of capacity) // Protein cavity identification and automatic subpocket decomposition

mhn-react

Modern Hopfield Network (MHN) for template relevance prediction

molfunc

fast functionalisation of molecules

Supramolecular_VAE

MMAML-rl

reptile-torch

PyTorch Implementation of Reptile

surge

A Fast Chemical Graph Generator