IJCAI 2021poster34 citations
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs
Christopher Morris, Matthias Fey, Nils Kriege
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.
Machine learning: General
BibTeX
@inproceedings{ijcai2021p618,
title = {The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs},
author = {Morris, Christopher and Fey, Matthias and Kriege, Nils},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {4543--4550},
year = {2021},
month = {8},
note = {Survey Track},
doi = {10.24963/ijcai.2021/618},
url = {https://doi.org/10.24963/ijcai.2021/618},
}