# awesome-graph-classification

**Repository Path**: oldshan/awesome-graph-classification

## Basic Information

- **Project Name**: awesome-graph-classification
- **Description**: A collection of important graph embedding, classification and representation learning papers with implementations.
- **Primary Language**: Unknown
- **License**: CC0-1.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-06-23
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Awesome Graph Classification
[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)
[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
![License](https://img.shields.io/github/license/benedekrozemberczki/awesome-graph-embedding.svg?color=blue&style=plastic)

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.

<p align="center">
  <img width="400" src="atlas.png">
</p>

## Contents  

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