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The Weisfeiler-Leman (WL) dimension of a graph is a measure for the inherent descriptive complexity of the graph. While originally derived from a combinatorial graph isomorphism test called the Weisfeiler-Leman algorithm, the WL dimension…

Discrete Mathematics · Computer Science 2019-04-16 Martin Grohe , Sandra Kiefer

In order to apply canonical labelling of graphs and isomorphism checking in interactive theorem provers, these checking algorithms must either be mechanically verified or their results must be verifiable by independent checkers. We analyze…

Logic in Computer Science · Computer Science 2023-06-22 Milan Banković , Ivan Drecun , Filip Marić

Circular coloring is a constraints satisfaction problem where colors are assigned to nodes in a graph in such a way that every pair of connected nodes has two consecutive colors (the first color being consecutive to the last). We study…

Disordered Systems and Neural Networks · Physics 2016-08-31 Christian Schmidt , Nils-Eric Guenther , Lenka Zdeborová

Graphs with a simple spectrum admit cubic-time isomorphism testing, yet we prove that for every natural number $k$, the $k$-Weisfeiler-Leman ($k$-WL) test cannot distinguish all non-isomorphic graphs with a simple spectrum. As the WL…

Machine Learning · Computer Science 2026-05-25 Snir Hordan , Nadav Dym , Tim Seppelt

We investigate the relationship between various isomorphism invariants for finite groups. Specifically, we use the Weisfeiler-Leman dimension (WL) to characterize, compare and quantify the effectiveness and complexity of invariants for…

Group Theory · Mathematics 2021-11-24 Jendrik Brachter , Pascal Schweitzer

We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph.…

Neural and Evolutionary Computing · Computer Science 2021-05-27 Jakob Bossek , Frank Neumann , Pan Peng , Dirk Sudholt

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

Many practical problems in almost all scientific and technological disciplines have been classified as computationally hard (NP-hard or even NP-complete). In life sciences, combinatorial optimization problems frequently arise in molecular…

Data Structures and Algorithms · Computer Science 2015-03-19 H. Jose Antonio Martin

This paper presents a new graph isomorphism invariant, called $\mathfrak{w}$-labeling, that can be used to design a polynomial-time algorithm for solving the graph isomorphism problem for various graph classes. For example, all…

Data Structures and Algorithms · Computer Science 2023-01-24 Alpár Jüttner , Péter Madarasi

This paper is devoted to advancing the theoretical understanding of the iterated immediate snapshot (IIS) complexity of the Weak Symmetry Breaking task (WSB). Our rather unexpected main theorem states that there exist infinitely many values…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-24 Dmitry N. Kozlov

Many applications, ranging from natural to social sciences, rely on graphlet analysis for the intuitive and meaningful characterization of networks employing micro-level structures as building blocks. However, it has not been thoroughly…

Social and Information Networks · Computer Science 2023-06-06 Colin Cleveland , Chin-Yen Lee , Shen-Fu Tsai , Wei-Hsuan Yu , Hsuan-Wei Lee

We prove that whenever $d=d(n)\to\infty$ and $n-d\to\infty$ as $n\to\infty$, then with high probability for any non-trivial initial colouring, the colour refinement algorithm distinguishes all vertices of the random regular graph…

Combinatorics · Mathematics 2026-02-20 Mikhail Isaev , Tamás Makai , Brendan McKay , Pawel Pralat , Jane Tan , Maksim Zhukovskii

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

In this paper, we first study a new extremal problem recently posed by Conlon and Tyomkyn~(arXiv: 2002.00921). Given a graph $H$ and an integer $k\geqslant 2$, let $f_{k}(n,H)$ be the smallest number of colors $c$ such that there exists a…

Combinatorics · Mathematics 2020-07-15 Zixiang Xu , Tao Zhang , Yifan Jing , Gennian Ge

The invariance to permutations of the adjacency matrix, i.e., graph isomorphism, is an overarching requirement for Graph Neural Networks (GNNs). Conventionally, this prerequisite can be satisfied by the invariant operations over node…

Machine Learning · Computer Science 2022-05-31 Zhongyu Huang , Yingheng Wang , Chaozhuo Li , Huiguang He

In this paper we study a family of discrete configuration spaces, the so-called protocol complexes, which are of utmost importance in theoretical distributed computing. Specifically, we consider questions of the existance of compliant…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-27 D. N. Kozlov

We examine ordered graphs, defined as graphs with linearly ordered vertices, from the perspective of homomorphisms (and colorings) and their complexities. We demonstrate the corresponding computational and parameterized complexities, along…

Computational Complexity · Computer Science 2025-12-01 Michal Čertík , Andreas Emil Feldmann , Jaroslav Nešetřil , Paweł Rzążewski

We initiate the study of applying the Combinatorial Nullstellensatz to the DP-coloring of graphs even though, as is well-known, the Alon-Tarsi theorem does not apply to DP-coloring. We define the notion of good covers of prime order which…

Combinatorics · Mathematics 2020-08-07 Hemanshu Kaul , Jeffrey A. Mudrock

Graph neural networks have become the de facto model for learning from structured data. However, the decision-making process of GNNs remains opaque to the end user, which undermines their use in safety-critical applications. Several…

Machine Learning · Computer Science 2026-05-12 Michele Fontanesi , Alessio Micheli , Marco Podda , Domenico Tortorella

Many graph problems are locally checkable: a solution is globally feasible if it looks valid in all constant-radius neighborhoods. This idea is formalized in the concept of locally checkable labelings (LCLs), introduced by Naor and…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-12 Alkida Balliu , Juho Hirvonen , Christoph Lenzen , Dennis Olivetti , Jukka Suomela
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