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

Implementation and experiments of graph embedding algorithms.

A distributed graph deep learning framework.

A curated list of community detection research papers with implementations.

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

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

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

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

A repository of pretty cool datasets that I collected for network science and machine learning research.

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

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

Representation learning for link prediction within social networks

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

A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)