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Seminal research in the field of graph neural networks (GNNs) has revealed a direct correspondence between the expressive capabilities of GNNs and the $k$-dimensional Weisfeiler-Leman ($k$WL) test, a widely-recognized method for verifying…

Machine Learning · Computer Science 2024-03-29 Matthias Lanzinger , Pablo Barceló

Graph kernels based on the $1$-dimensional Weisfeiler-Leman algorithm and corresponding neural architectures recently emerged as powerful tools for (supervised) learning with graphs. However, due to the purely local nature of the…

Data Structures and Algorithms · Computer Science 2020-10-20 Christopher Morris , Gaurav Rattan , Petra Mutzel

Graph isomorphism, a classical algorithmic problem, determines whether two input graphs are structurally identical or not. Interestingly, it is one of the few problems that is not yet known to belong to either the P or NP-complete…

Data Structures and Algorithms · Computer Science 2024-10-01 Sourav Dutta , Arnab Bhattacharya

We prove that the combinatorial Weisfeiler-Leman algorithm of dimension $(3k+4)$ is a complete isomorphism test for the class of all graphs of rank width at most $k$. Rank width is a graph invariant that, similarly to tree width, measures…

Data Structures and Algorithms · Computer Science 2023-05-30 Martin Grohe , Daniel Neuen

The Weisfeiler--Lehman (WL) test is a fundamental iterative algorithm for checking isomorphism of graphs. It has also been observed that it underlies the design of several graph neural network architectures, whose capabilities and…

Machine Learning · Computer Science 2025-06-13 Valentino Delle Rose , Alexander Kozachinskiy , Cristóbal Rojas , Mircea Petrache , Pablo Barceló

It is unknown whether two graphs can be tested for isomorphism in polynomial time. A classical approach to the Graph Isomorphism Problem is the d-dimensional Weisfeiler-Lehman algorithm. The d-dimensional WL-algorithm can distinguish many…

Combinatorics · Mathematics 2010-12-10 Harm Derksen

The Weisfeiler-Lehman (WL) test is a classical procedure for graph isomorphism testing. The WL test has also been widely used both for designing graph kernels and for analyzing graph neural networks. In this paper, we propose the…

Machine Learning · Computer Science 2022-02-08 Samantha Chen , Sunhyuk Lim , Facundo Mémoli , Zhengchao Wan , Yusu Wang

We provide a criterion to distinguish two graphs which are indistinguishable by $2$-dimensional Weisfeiler-Lehman algorithm for almost all graphs. Haemers conjectured that almost all graphs are identified by their spectrum. Our approach…

Combinatorics · Mathematics 2025-11-21 Wei Wang , Da Zhao

The Weisfeiler-Leman algorithm ($1$-WL) is a well-studied heuristic for the graph isomorphism problem. Recently, the algorithm has played a prominent role in understanding the expressive power of message-passing graph neural networks…

Machine Learning · Computer Science 2024-05-29 Billy J. Franks , Christopher Morris , Ameya Velingker , Floris Geerts

The classical Weisfeiler-Lehman method WL[2] uses edge colors to produce a powerful graph invariant. It is at least as powerful in its ability to distinguish non-isomorphic graphs as the most prominent algebraic graph invariants. It…

Data Structures and Algorithms · Computer Science 2017-04-05 Martin Fürer

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…

Machine Learning · Computer Science 2021-11-23 Christopher Morris , Matthias Fey , Nils M. Kriege

In this paper, we relate a beautiful theory by Lov\'asz with a popular heuristic algorithm for the graph isomorphism problem, namely the color refinement algorithm and its k-dimensional generalization known as the Weisfeiler-Leman…

Data Structures and Algorithms · Computer Science 2018-05-23 Holger Dell , Martin Grohe , Gaurav Rattan

In this paper, we show that the $(3k+4)$-dimensional Weisfeiler--Leman algorithm can identify graphs of treewidth $k$ in $O(\log n)$ rounds. This improves the result of Grohe & Verbitsky (ICALP 2006), who previously established the…

Data Structures and Algorithms · Computer Science 2024-04-26 Michael Levet , Puck Rombach , Nicholas Sieger

The classical Weisfeiler-Leman algorithm aka color refinement is fundamental for graph learning with kernels and neural networks. Originally developed for graph isomorphism testing, the algorithm iteratively refines vertex colors. On many…

Machine Learning · Computer Science 2022-12-09 Franka Bause , Nils M. Kriege

The combinatorial refinement techniques have proven to be an efficient approach to isomorphism testing for particular classes of graphs. If the number of refinement rounds is small, this puts the corresponding isomorphism problem in a…

Combinatorics · Mathematics 2024-09-17 Laurence Kluge

Our starting point is the observation that if graphs in a class C have low descriptive complexity in first order logic, then the isomorphism problem for C is solvable by a fast parallel algorithm (essentially, by a simple combinatorial…

Computational Complexity · Computer Science 2007-05-23 Martin Grohe , Oleg Verbitsky

An origin of the multidimensional Weisfeiler-Leman algorithm goes back to a refinement procedure of deep stabilization, introduced by B. Weisfeiler in a paper included in the collective monograph ``On construction and identification of…

Combinatorics · Mathematics 2023-11-17 Gang Chen , Qing Ren , Ilia Ponomarenko

In this paper we combine many of the standard and more recent algebraic techniques for testing isomorphism of finite groups (GpI) with combinatorial techniques that have typically been applied to Graph Isomorphism. In particular, we show…

Computational Complexity · Computer Science 2019-05-08 Peter A. Brooksbank , Joshua A. Grochow , Yinan Li , Youming Qiao , James B. Wilson

We present a novel approach for graph classification based on tabularizing graph data via new variants of the Weisfeiler-Leman algorithm and then applying methods for tabular data. The variants are obtained by modifying the underlying…

Machine Learning · Computer Science 2026-05-25 Reijo Jaakkola , Tomi Janhunen , Antti Kuusisto , Magdalena Ortiz , Matias Selin , Mantas Šimkus

In this paper, we show that computing canonical labelings of graphs of bounded rank-width is in $\textsf{TC}^{2}$. Our approach builds on the framework of K\"obler & Verbitsky (CSR 2008), who established the analogous result for graphs of…

Data Structures and Algorithms · Computer Science 2024-04-26 Michael Levet , Puck Rombach , Nicholas Sieger