Overviews of Graph Classification and Network Clustering methods

Thanks to Sebastian Raschka I am able to share this great GitHub overview page of relevant graph classification techniques, and the scientific papers behind them. The overview divides the algorithms into four groups:

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

Moreover, the overview contains links to similar collections on community detectionclassification/regression trees and gradient boosting papers with implementations.

As well as a link to relevant graph classification benchmark datasets.

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