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2s-agcn

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

advssl

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning

alchemy

ampligraph

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

asne

A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).

attention_in_graph

attention mechanism for graph classification, significant sub-graph mining, graph disstillation

attentionwalk

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

augmented-gcn

autogcn

autogl

An autoML framework & toolkit for machine learning on graphs.

autogl-1

AutoGL is a graph learning framework with automatic machine learning techniques, and the 6th solution for AutoGraph Challenge@KDD'20

autograph2020

The 2nd place solution for KDD Cup AutoGraph2020

awesome-architecture-search

A curated list of awesome architecture search resources

awesome-graph-classification

A collection of important graph embedding, classification and representation learning papers with implementations.

awesome-graph-contrastive-learning

Collection of resources related with Graph Contrastive Learning.

awesome-graph-representation-learning

A curated list of awesome graph representation learning.

awesome-network-embedding

A curated list of network embedding techniques.

awesome-self-supervised-learning-for-graphs

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

benchmarking-gnns

Repository for benchmarking graph neural networks

benchmarking-gnns-1

Repository for benchmarking graph neural networks

bsd-gcn

The tensorflow code of the paper"Dual-Graph Convolutional Network Based on Band Attention and Sparse Constraint for Hyperspectral Band Selection"

c-swm

Contrastive Learning of Structured World Models

capsgnn

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

cayleynet

Graph Convolutional Neural Networks with Complex Rational Spectral Filters

channelnets

Tensorflow Implementation of ChannelNets (NeurIPS 18)

cifar-superpixel

Superpixel for CIFAR dataset

clustergcn

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

cnn_graph

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

cogdl

CogDL: An Extensive Research Toolkit for Graphs

comparision-of-graphical-models-

Comparison of graph models: GCN, GAT and GGNN. We use these models to predict objects in the image using the context information provided by Knowledge Graphs