Weisfeiler and Lemanâ€™s Unlikely Journey from Graph Isomorphism to Neural Networks (Invited Talk)
The Weisfeiler-Leman algorithm is a well-known combinatorial graph isomorphism test going back to work of Weisfeiler and Leman in the late 1960s. The algorithm has a surprising number of seemingly unrelated characterisations in terms of logic, algebra, linear and semi-definite programming, and graph homomorphisms. Due to its simplicity and efficiency, it is an important subroutine of all modern graph isomorphism tools. In recent years, further applications in linear optimisation, probabilistic inference, and machine learning have surfaced. In the first part of my talk, I will give an introduction to the Weisfeiler-Leman algorithm and its various characterisations. In the second part I will speak about its applications, in particular about recent work relating the algorithm to graph neural networks.
Weisfeiler adn Leman algorithm
Graph isomorphism
Neural network
logic
algebra
linear and semi-definite programming
Theory of computation~Discrete optimization
Mathematics of computing~Graph algorithms
2:1-2:1
Invited Talk
Martin
Grohe
Martin Grohe
RWTH Aachen University, Germany
https://www.lics.rwth-aachen.de/~grohe
https://orcid.org/0000-0002-0292-9142
10.4230/LIPIcs.STACS.2020.2
Martin Grohe
Creative Commons Attribution 3.0 Unported license
https://creativecommons.org/licenses/by/3.0/legalcode