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https://github.com/benedekrozemberczki/awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
https://github.com/benedekrozemberczki/awesome-graph-classification
List: awesome-graph-classification
attention-mechanism classification-algorithm deep-graph-kernels deepwalk graph-attention-model graph-attention-networks graph-classification graph-convolutional-networks graph-embedding graph-kernel graph-kernels graph-representation-learning graph2vec kernel-methods netlsd network-embedding node-embedding node2vec structural-attention weisfeiler-lehman
Last synced: about 1 month ago
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A collection of important graph embedding, classification and representation learning papers with implementations.
- Host: GitHub
- URL: https://github.com/benedekrozemberczki/awesome-graph-classification
- Owner: benedekrozemberczki
- License: cc0-1.0
- Created: 2018-07-14T12:13:44.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-03-18T12:10:08.000Z (over 1 year ago)
- Last Synced: 2024-05-23T04:10:59.786Z (6 months ago)
- Topics: attention-mechanism, classification-algorithm, deep-graph-kernels, deepwalk, graph-attention-model, graph-attention-networks, graph-classification, graph-convolutional-networks, graph-embedding, graph-kernel, graph-kernels, graph-representation-learning, graph2vec, kernel-methods, netlsd, network-embedding, node-embedding, node2vec, structural-attention, weisfeiler-lehman
- Language: Python
- Homepage:
- Size: 1.79 MB
- Stars: 4,706
- Watchers: 217
- Forks: 744
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: contributing.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: code-of-conduct.md
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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)
[![repo size](https://img.shields.io/github/repo-size/benedekrozemberczki/awesome-graph-classification.svg)](https://github.com/benedekrozemberczki/awesome-graph-classification/archive/master.zip) [![benedekrozemberczki](https://img.shields.io/twitter/follow/benrozemberczki?style=social&logo=twitter)](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.
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## 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)