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A collection of important graph embedding, classification and representation learning papers with implementations.

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Awesome Graph Classification

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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].

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


  1. Matrix Factorization
  2. Spectral and Statistical Fingerprints
  3. Deep Learning
  4. Graph Kernels

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