The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs
Christopher Morris, Matthias Fey, Nils Kriege
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Survey Track. Pages 4543-4550.
https://doi.org/10.24963/ijcai.2021/618
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.
Keywords:
Machine learning: General