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3d_scaffold

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-cheminformatics

A curated list of Cheminformatics libraries and software.

awesome-graph-contrastive-learning

Collection of resources related with Graph Contrastive Learning.

awesome-graph-self-supervised-learning

Awesome Graph Self-Supervised Learning

awesome-self-supervised-gnn

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

awesome-self-supervised-learning-for-graphs

A curated list for awesome self-supervised learning for graphs.

chemprop

Message Passing Neural Networks for Molecule Property Prediction

comparisonsdgm

Comparisons of Drug Generation Models

contrastive-learning-papers-codes

A comprehensive list of Awesome Contrastive Learning Papers&Codes.Research include, but are not limited to: CV, NLP, Audio, Video, Multimodal, Graph, Language, etc.

coronavirus_data

deep_scaffold

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

develop

diffpool

drug_design_models

This project is a reimplementation of the models introduced in the following papers: "Multiobjective de novo drug design with recurrent neural networks and nondominated sorting", "REINVENT 2.0: An AI Tool for De Novo Drug Design", "Hierarchical generation of molecular graphs using structural motifs", "Mol-CycleGAN: a generative model for molecular optimization", "Multi-objective de novo drug design with conditional graph generative model" and "Graph convolutional policy network for goal-directed molecular graph generation".

g-schnet

G-SchNet - a generative model for 3d molecular structures

gcc

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

gcl

List of Publications in Graph Contrastive Learning

gnn-recommender-systems

An index of recommendation algorithms that are based on Graph Neural Networks.

gnnpapers

Must-read papers on graph neural networks (GNN)

google-research

Google Research

gpt-gnn

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

graph-embedding

Four network embedding algorithms(deepwalk, node2vec, TADW ,LINE) for two datasets(Cora, Tencent Weibo)

graph-neural-networks-for-drug-discovery

graphinvent

Graph neural networks for molecular design.

hgraph2graph

Hierarchical Generation of Molecular Graphs using Structural Motifs

how-do-vits-work

(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"

icml18-jtnn

Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

l2p-gnn

Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"