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In this paper we show lower bounds for a certain large class of algorithms solving the Graph Isomorphism problem, even on expander graph instances. Spielman [25] shows an algorithm for isomorphism of strongly regular expander graphs that…

Computational Complexity · Computer Science 2016-10-31 Aaron Snook , Grant Schoenebeck , Paolo Codenotti

Various recent proposals increase the distinguishing power of Graph Neural Networks GNNs by propagating features between $k$-tuples of vertices. The distinguishing power of these "higher-order'' GNNs is known to be bounded by the…

Machine Learning · Computer Science 2021-06-15 Pablo Barceló , Floris Geerts , Juan Reutter , Maksimilian Ryschkov

We investigate algorithms for canonical labelling of site graphs, i.e. graphs in which edges bind vertices on sites with locally unique names. We first show that the problem of canonical labelling of site graphs reduces to the problem of…

Discrete Mathematics · Computer Science 2013-06-12 Nicolas Oury , Michael Pedersen , Rasmus Petersen

In this paper we resolve the complexity of the isomorphism problem on all but finitely many of the graph classes characterized by two forbidden induced subgraphs. To this end we develop new techniques applicable for the structural and…

Discrete Mathematics · Computer Science 2014-11-10 Pascal Schweitzer

Stars' chemical signatures provide invaluable insights into stellar cluster formation. This study utilized the Weisfeiler-Lehman (WL) Graph Kernel to examine a 15-dimensional elemental abundance space. Through simulating chemical…

Astrophysics of Galaxies · Physics 2023-06-27 Yuan-Sen Ting , Bhavesh Sharma

Determining whether two graphs are structurally identical is a fundamental problem with applications spanning mathematics, computer science, chemistry, and network science. Despite decades of study, graph isomorphism remains a challenging…

Computational Physics · Physics 2026-04-10 Sara Najem , Amer E. Mouawad

We give the first polynomial-time algorithms on graphs of bounded maximum induced matching width (mim-width) for problems that are not locally checkable. In particular, we give $n^{\mathcal{O}(w)}$-time algorithms on graphs of mim-width at…

Data Structures and Algorithms · Computer Science 2017-09-29 Lars Jaffke , O-joung Kwon , Jan Arne Telle

We discuss the definability of finite graphs in first-order logic with two relation symbols for adjacency and equality of vertices. The logical depth $D(G)$ of a graph $G$ is equal to the minimum quantifier depth of a sentence defining $G$…

Combinatorics · Mathematics 2013-04-30 Oleg Pikhurko , Oleg Verbitsky

[PLEASE SEE COMMENT] We consider the isomorphism problem for finite abelian groups and finite meta-cyclic groups. We prove that for a dense set of positive integers $n$, isomorphism testing for abelian groups of black-box type of order $n$…

Group Theory · Mathematics 2021-09-03 Heiko Dietrich , James B. Wilson

The Weisfeiler-Lehman graph kernels are among the most prevalent graph kernels due to their remarkable time complexity and predictive performance. Their key concept is based on an implicit comparison of neighborhood representing trees with…

Machine Learning · Computer Science 2021-01-21 Till Hendrik Schulz , Tamás Horváth , Pascal Welke , Stefan Wrobel

In this paper we consider the problem of testing whether two finite groups are isomorphic. Whereas the case where both groups are abelian is well understood and can be solved efficiently, very little is known about the complexity of…

Quantum Physics · Physics 2021-10-05 François Le Gall

Today we have a good theoretical understanding of the representational power of Graph Neural Networks (GNNs). For example, their limitations have been characterized in relation to a hierarchy of Weisfeiler-Lehman (WL) isomorphism tests.…

Machine Learning · Computer Science 2023-03-08 Mohammad Sadegh Akhondzadeh , Vijay Lingam , Aleksandar Bojchevski

Graph is an usual representation of relational data, which are ubiquitous in manydomains such as molecules, biological and social networks. A popular approach to learningwith graph structured data is to make use of graph kernels, which…

Machine Learning · Computer Science 2022-08-02 Dai Hai Nguyen , Canh Hao Nguyen , Hiroshi Mamitsuka

This work generalizes graph neural networks (GNNs) beyond those based on the Weisfeiler-Lehman (WL) algorithm, graph Laplacians, and diffusions. Our approach, denoted Relational Pooling (RP), draws from the theory of finite partial…

Machine Learning · Computer Science 2019-05-16 Ryan L. Murphy , Balasubramaniam Srinivasan , Vinayak Rao , Bruno Ribeiro

The ability of a graph neural network (GNN) to leverage both the graph topology and graph labels is fundamental to building discriminative node and graph embeddings. Building on previous work, we theoretically show that edGNN, our model for…

Machine Learning · Computer Science 2019-12-05 Guillaume Jaume , An-phi Nguyen , María Rodríguez Martínez , Jean-Philippe Thiran , Maria Gabrani

In this paper, we present two main results. First, by only one conjecture (Conjecture 2.9) for recognizing a vertex symmetric graph, which is the hardest task for our problem, we construct an algorithm for finding an isomorphism between two…

Data Structures and Algorithms · Computer Science 2017-06-29 Caishi Fang

In this paper, motivated by a question posed in \cite{AH}, we introduce strongly biconvex graphs as a subclass of weakly chordal and bipartite graphs. We give a linear time algorithm to find an induced matching for such graphs and we prove…

Commutative Algebra · Mathematics 2019-05-08 Sara Saeedi Madani , Dariush Kiani

This is the second paper in a series of two. The goal of the series is to give a polynomial time algorithm for the $4$-coloring problem and the $4$-precoloring extension problem restricted to the class of graphs with no induced six-vertex…

Combinatorics · Mathematics 2018-02-09 Maria Chudnovsky , Sophie Spirkl , Mingxian Zhong

Enumerating minimal dominating sets with polynomial delay in bipartite graphs is a long-standing open problem. To date, even the subcase of chordal bipartite graphs is open, with the best known algorithm due to Golovach, Heggernes, Kant\'e,…

Data Structures and Algorithms · Computer Science 2025-08-05 Emanuel Castelo , Oscar Defrain , Guilherme C. M. Gomes

Link prediction is one important application of graph neural networks (GNNs). Most existing GNNs for link prediction are based on one-dimensional Weisfeiler-Lehman (1-WL) test. 1-WL-GNNs first compute node representations by iteratively…

Machine Learning · Computer Science 2022-06-22 Yang Hu , Xiyuan Wang , Zhouchen Lin , Pan Li , Muhan Zhang
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