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.

Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)

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

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

This repository contains the "tensorflow" implementation of our paper "graph2vec: Learning distributed representations of graphs".

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".

Theano implementation of GloVe for graphs

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)

graph2vec

Graph and Nodes embeddings for downstream tasks

Understanding Large Social Networks using LINE paper.

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

Combine ideas of Graph2Vec with differentiable vocabulary extractor (GCN) and differentiable graph embedder (Kron and Loukas coarsening)

An exchanger for nebula graph data to vector db milvus.

No description available

An unsupervised model for learning distributed graph inspired by Deep Graph Kernels (Yanardag and Vishwanathan) and Graph2Vec (Narayanan et al) for labelled and unlabelled graphs (as well as directed/undirected)

Graph2vec

A simple, naive implementation of graph2vec algorithm using word2vec algorithm

No description available

No description available

Classification of chemical compounds according to their mutagenic effect on bacteria via graph2vec, feed-forward neural networks, and logistic regression.