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Color refinement is a classical technique used to show that two given graphs G and H are non-isomorphic; it is very efficient, although it does not succeed on all graphs. We call a graph G amenable to color refinement if it succeeds in…

Computational Complexity · Computer Science 2015-05-05 V. Arvind , Johannes Köbler , Gaurav Rattan , Oleg Verbitsky

Formulating optimization problems for industrial applications demands significant manual effort and domain expertise. While Large Language Models (LLMs) show promise in automating this process, evaluating their performance remains difficult…

Machine Learning · Computer Science 2025-11-03 Zhuohan Wang , Ziwei Zhu , Ziniu Li , Congliang Chen , Yizhou Han , Yufeng Lin , Zhihang Lin , Angyang Gu , Xinglin Hu , Ruoyu Sun , Tian Ding

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

The problem of graph isomorphism is an important but challenging problem in the field of graph analysis, for example: analyzing the similarity of two chemical molecules, or studying the expressive ability of graph neural networks. WL test…

Other Computer Science · Computer Science 2024-02-14 Wanghan Xu

The graph isomorphism problem is a main problem which has numerous applications in different fields. Thus, finding an efficient and easy to implement method to discriminate non-isomorphic graphs is valuable. In this paper, a new method is…

Combinatorics · Mathematics 2016-11-08 Ameneh Farhadian

The complexity of graph isomorphism (GraphIso) is a famous unresolved problem in theoretical computer science. For graphs $G$ and $H$, it asks whether they are the same up to a relabeling of vertices. In 1981, Lubiw proved that list…

Discrete Mathematics · Computer Science 2016-11-03 Pavel Klavik , Dušan Knop , Peter Zeman

This paper presents the Persistent Weisfeiler-Lehman Random walk scheme (abbreviated as PWLR) for graph representations, a novel mathematical framework which produces a collection of explainable low-dimensional representations of graphs…

Machine Learning · Computer Science 2022-08-30 Sun Woo Park , Yun Young Choi , Dosang Joe , U Jin Choi , Youngho Woo

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

The Graph Isomorphism problem has both theoretical and practical interest. In this paper we present an algorithm, called conauto-1.2, that efficiently tests whether two graphs are isomorphic, and finds an isomorphism if they are. This…

Data Structures and Algorithms · Computer Science 2011-06-23 Jose Luis Lopez-Presa , Antonio Fernandez Anta

Many complex questions in biology, physics, and mathematics can be mapped to the graph isomorphism problem and the closely related graph automorphism problem. In particular, these problems appear in the context of network visualization,…

Data Structures and Algorithms · Computer Science 2012-11-14 Charo I. Del Genio , Thilo Gross

Graph neural networks have been widely used on modeling graph data, achieving impressive results on node classification and link prediction tasks. Yet, obtaining an accurate representation for a graph further requires a pooling function…

Machine Learning · Computer Science 2021-06-29 Jinheon Baek , Minki Kang , Sung Ju Hwang

Learning to optimize is a rapidly growing area that aims to solve optimization problems or improve existing optimization algorithms using machine learning (ML). In particular, the graph neural network (GNN) is considered a suitable ML model…

Machine Learning · Computer Science 2023-05-29 Ziang Chen , Jialin Liu , Xinshang Wang , Jianfeng Lu , Wotao Yin

The Weisfeiler-Leman dimension of a graph $G$ is the least number $k$ such that the $k$-dimensional Weisfeiler-Leman algorithm distinguishes $G$ from every other non-isomorphic graph. The dimension is a standard measure of the descriptive…

Computational Complexity · Computer Science 2024-11-18 Moritz Lichter , Simon Raßmann , Pascal Schweitzer

Building on work of Cai, F\"urer, and Immerman \cite{CFI92}, we show two hardness results for the Graph Isomorphism problem. First, we show that there are pairs of nonisomorphic $n$-vertex graphs $G$ and $H$ such that any sum-of-squares…

Computational Complexity · Computer Science 2014-01-13 Ryan O'Donnell , John Wright , Chenggang Wu , Yuan Zhou

We claimed that there is a polynomial algorithm to test if two graphs are isomorphic. But the algorithm is wrong. It only tests if the adjacency matrices of two graphs have the same eigenvalues. There is a counterexample of two…

Computational Complexity · Computer Science 2022-10-18 Reiner Czerwinski

The Weisfeiler-Leman (WL) dimension is an established measure for the inherent descriptive complexity of graphs and relational structures. It corresponds to the number of variables that are needed and sufficient to define the object of…

Discrete Mathematics · Computer Science 2024-02-06 Sandra Kiefer , Daniel Neuen

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

In the past decades for more and more graph classes the Graph Isomorphism Problem was shown to be solvable in polynomial time. An interesting family of graph classes arises from intersection graphs of geometric objects. In this work we show…

Data Structures and Algorithms · Computer Science 2016-06-23 Daniel Neuen

The pairwise interaction paradigm of graph machine learning has predominantly governed the modelling of relational systems. However, graphs alone cannot capture the multi-level interactions present in many complex systems and the expressive…

Machine Learning · Computer Science 2021-06-15 Cristian Bodnar , Fabrizio Frasca , Yu Guang Wang , Nina Otter , Guido Montúfar , Pietro Liò , Michael Bronstein

As it follows from G\"odel's incompleteness theorems, any consistent formal system of axioms and rules of inference should imply a true unprovable statement. Actually, this fundamental principle can be efficiently applicable in…

Data Structures and Algorithms · Computer Science 2020-11-25 Roman Galay , Daniil Kalistratov