The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4543-4550.
https://doi.org/10.24963/ijcai.2021/618
Keywords
- Machine learning: General
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.
@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 = {Prof. 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},
}
TY - CPAPER TI - The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs AU - Morris, Christopher AU - Fey, Matthias AU - Kriege, Nils T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 4543 EP - 4550 DO - 10.24963/ijcai.2021/618 UR - https://doi.org/10.24963/ijcai.2021/618 ER -Copied
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