Weisfeiler-Lehman Graph Kernels

Main content

Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, Karsten Borgwardt

Weisfeiler-Lehman Graph Kernels

Code

This zip (ZIP, 580 KB) archive contains Matlab scripts to compute various graph kernels for graphs with unlabeled or categorically labeled nodes, such as the random walk, shortest path, graphlet, several instances of Weisfeiler-Lehman or other subtree kernels. For a more detailed list of available kernels please consult the README in the archive.

Datasets

You can also download the graph data sets MUTAG, NCI1, NCI109, ENZYMES, and D&D (all in Matlab format) as a zip (ZIP, 10.1 MB) archive. This archive also contains a README describing the data sets and explaining their usage.

Download the graph data sets MUTAG, NCI1, NCI109, ENZYMES, and DD (all in Matlab format) as a zip (ZIP, 10.1 MB) or a tar.gz (GZ, 10.1 MB) archive. The archive also contains a README describing the data sets and explaining their usage. Download the Matlab scripts for the WL subtree, edge and shortest path kernels as a zip (ZIP, 8 KB) or a tar.gz (GZ, 4 KB) archive. This archive also contains a README explaining the usage of the scripts.

Publication

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Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn and Karsten M. Borgwardt
Weisfeiler-Lehman graph kernels,
Journal of Machine Learning Research (JMLR) 12(Sep):2539−2561, 2011. (Online)

Further information and the code can be found on the project page.

@article{Shervashidze-2011-JMLR,
author = {Shervashidze, Nino and Schweitzer, Pascal and van Leeuwen, Erik Jan and Mehlhorn, Kurt and Borgwardt, Karsten M.},
title = {Weisfeiler-{L}ehman {G}raph {K}ernels},
journal = {The Journal of Machine Learning Research},
issue_date = {2/1/2011},
volume = {12},
month = nov,
year = {2011},
issn = {1532-4435},
pages = {2539--2561},
numpages = {23},
url = {http://www.jmlr.org/papers/v12/shervashidze11a.html},
publisher = {JMLR.org},
}

Contact  Karsten Borgwardt for questions.

 
 
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