awesome-graph-classification

# Awesome Graph Classification [](https://twitter.com/intent/follow?screen_name=benrozemberczki) 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]](https://github.com/shiruipan/graph_datasets). Similar collections about [community detection](https://github.com/benedekrozemberczki/awesome-community-detection), [classification/regression tree](https://github.com/benedekrozemberczki/awesome-decision-tree-papers), [fraud detection](https://github.com/benedekrozemberczki/awesome-fraud-detection-papers), [Monte Carlo tree search](https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers), and [gradient boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers) papers with implementations.

------------------------------------------------- ## Contents 1. [Matrix Factorization](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/matrix_factorization.md) 2. [Spectral and Statistical Fingerprints](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/fingerprints.md) 3. [Deep Learning](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/deep_learning.md) 4. [Graph Kernels](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/kernels.md) ----------------------------------------------- **License** - [CC0 Universal](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/LICENSE)