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arXiv · 2105.05911

The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs

Christopher Morris·Matthias Fey·Nils M. Kriege
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Abstract

In recent years, algorithms and neural architectures based on the Weisfeiler-Leman algorithm, a well-known heuristic for the graph isomorphism problem, emerged as a powerful tool for (supervised) machine learning with graphs and relational data. Here, we give a comprehensive overview of the algorithm's use in a machine learning setting. We discuss the theoretical background, show how to use it for supervised graph- and node classification, discuss recent extensions, and its connection to neural architectures. Moreover, we give an overview of current applications and future directions to stimulate research.

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BibTeXRIS

Christopher Morris, Matthias Fey, Nils M. Kriege. 2021-05-12. The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. https://arxiv.org/abs/2105.05911

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