31 lines
2.4 KiB
Plaintext
31 lines
2.4 KiB
Plaintext
# Awesome Graph Classification
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[](https://github.com/sindresorhus/awesome)
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[](http://makeapullrequest.com)
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[](https://github.com/benedekrozemberczki/awesome-graph-classification/archive/master.zip) [](https://twitter.com/intent/follow?screen_name=benrozemberczki)
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A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations.
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Relevant graph classification benchmark datasets are available [[here]](https://github.com/shiruipan/graph_datasets).
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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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<p align="center">
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<img width="400" src="atlas.png">
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</p>
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-------------------------------------------------
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## Contents
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1. [Matrix Factorization](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/matrix_factorization.md)
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2. [Spectral and Statistical Fingerprints](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/fingerprints.md)
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3. [Deep Learning](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/deep_learning.md)
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4. [Graph Kernels](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/chapters/kernels.md)
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-----------------------------------------------
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**License**
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- [CC0 Universal](https://github.com/benedekrozemberczki/awesome-graph-classification/blob/master/LICENSE)
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