pyGPs is an object-oriented Python package for Gaussian processes for machine learning. Download pyGPs HERE or view it on GitHub:

Coinciding Walk Kernel

The coinciding walk kernel is a kernel among the nodes of a graph. It can be used for node label classification. The implementation is available HERE.

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Propagation Kernels

Propagation Kernels are a framework to compute a kernel between graphs. They can be used for graph classification for labaled, attributed, unlabaled, and grid graphs. A MATLAB implementation is available here: A Python implementation for labaled and unlabaled graphs is part of pyGPs or can be directly found HERE.

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