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

Awesome Graph Classification

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations.

Relevant graph classification benchmark datasets are available [here].

Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations.

Contents

1. Matrix Factorization
2. Spectral and Statistical Fingerprints
3. Deep Learning
4. Graph Kernels