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

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

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

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

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

Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Minimum-distortion embedding with PyTorch

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

Representation learning on dynamic graphs using self-attention networks

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

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

DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"

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)

Python based Graph Propagation algorithm, DeepWalk to evaluate and compare preference propagation algorithms in heterogeneous information networks from user item relation ship.

A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".