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

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

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 Classification Using Structural Attention" (KDD 2018).

Smart contract vulnerability detection using graph neural network (DR-GCN).

An implementation of "EdMot: An Edge Enhancement Approach for Motif-aware Community Detection" (KDD 2019)

A sparsity aware implementation of "Binarized Attributed Network Embedding" (ICDM 2018).

A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

Visual Analysis of Temporal Summaries in Dynamic Graphs (IEEE TVCG)

Graph and Nodes embeddings for downstream tasks

This project contain implementation the system, proposed in the "Adapting the Graph2Vec Approach to Dependency Trees for NLP Tasks" (O. Durandin, A. Malafeev), and presented in the AIST-2019 Conference