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equidock_public

equifold

Official code repository for EquiFold

equiformer

[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

equigendyna

We propose an SO(3) equivariant deep dynamical model (EqDDM) for motion prediction that learns a structured representation of the input space in the sense that the embedding varies with symmetry transformations. EqDDM is equipped with equivariant networks to parameterize the state-space emission and transition models. We demonstrate the superior predictive performance of the proposed model on various motion data.

espaloma

Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196

evol_div

Structural scores from multiple sequence alignments

fbgan

freed

Fragment-based generative RL with Explorative Experience replay for Drug design (FREED)

g-meta

Graph meta learning via local subgraphs (NeurIPS 2020)

g2g-transformer

Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”

gcc

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

gcn-for-structure-and-function

Code for reproducing results of "Unsupervised embeddings is all you need for protein function prediction"

gdc

Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)

gdl

Code for Online Graph Dictionary Learning

gdrl

Grokking Deep Reinforcement Learning

gemnet_pytorch

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

geomol

geoppi

ggnn.pytorch

A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)

gmnn

Graph Markov Neural Networks

gnn-lspe

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)

gnnaskernel

Source code for From Stars to Subgraphs

google-research

Google Research

gp-vae

graph-bert

Source code of Graph-Bert

graph-generation

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

graph-substructure-networks

graph2seq

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

graphformers

graphite

Code for Graphite iterative graph generation