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

Features

  • Explainable Classification of Brain Networks via Contrast Subgraphs
  • A Simple Yet Effective Baseline for Non-Attribute Graph Classification
  • Multi-Graph Multi-Label Learning Based on Entropy
  • Joint Structure Feature Exploration
  • A Scalable Approach to Size-Independent Network Similarity
  • Regularization for Multi-Task Graph Classification

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Awesome Graph Classification Screenshot 1

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Categories

Documentation, Libraries, Deep Learning Frameworks

License

Creative Commons Attribution License

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Additional Project Details

Programming Language

Python

Related Categories

Python Documentation Software, Python Libraries, Python Deep Learning Frameworks

Registered

2021-12-16
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