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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

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

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

It has long been known that a vertex-transitive graph $\Gamma$ is isomorphic to a double coset graph $\text{Cos}(G,H,S)$ of a transitive group $G\le\text{Aut}(\Gamma)$, a vertex stabilizer $H\le G$, and some subset $S\subseteq G$. We show…

Combinatorics · Mathematics 2024-07-03 Rachel Barber , Ted Dobson

We propose a novel method using a quantum annealer -- an analog quantum computer based on the principles of quantum adiabatic evolution -- to solve the Graph Isomorphism problem, in which one has to determine whether two graphs are…

Quantum Physics · Physics 2013-05-30 Itay Hen , A. P. Young

This paper studies the problem of detecting anomalous graphs using a machine learning model trained on only normal graphs, which has many applications in molecule, biology, and social network data analysis. We present a self-discriminative…

Machine Learning · Computer Science 2023-10-11 Jinyu Cai , Yunhe Zhang , Jicong Fan

Deep learning models have achieved huge success in numerous fields, such as computer vision and natural language processing. However, unlike such fields, it is hard to apply traditional deep learning models on the graph data due to the…

Machine Learning · Computer Science 2019-10-01 Lin Meng , Jiawei Zhang

Symmetries of combinatorial objects are known to complicate search algorithms, but such obstacles can often be removed by detecting symmetries early and discarding symmetric subproblems. Canonical labeling of combinatorial objects…

Data Structures and Algorithms · Computer Science 2013-05-01 Hadi Katebi , Karem A. Sakallah , Igor L. Markov

Subgraph Isomorphism uses a small graph as a pattern to identify within a larger graph a set of vertices that have matching edges. This paper addresses a logic program written in Prolog for a specific relatively complex graph pattern for…

Logic in Computer Science · Computer Science 2026-01-14 Claire Y. Yin , Peter M. Kogge

In the $(G,H)$-isomorphism game, a verifier interacts with two non-communicating players (called provers) by privately sending each of them a random vertex from either $G$ or $H$, whose aim is to convince the verifier that two graphs $G$…

Combinatorics · Mathematics 2020-04-24 Laura Mančinska , David E. Roberson , Antonios Varvitsiotis

Subgraph isomorphism is a well-known NP-hard problem which is widely used in many applications, such as social network analysis and knowledge graph query. Its performance is often limited by the inherent hardness. Several insightful works…

Databases · Computer Science 2021-04-21 Li Zeng , Yan Jiang , Weixin Lu , Lei Zou

Given a graph $G$, the graph $[G]$ obtained by adding, for each pair of vertices of $G$, a unique vertex adjacent to both vertices is called the binding graph of $G$. In this work, we show that the class of binding graphs is…

Combinatorics · Mathematics 2024-08-27 Rui Xue

In this paper, we study the graph classification problem from the graph homomorphism perspective. We consider the homomorphisms from $F$ to $G$, where $G$ is a graph of interest (e.g. molecules or social networks) and $F$ belongs to some…

Machine Learning · Computer Science 2020-07-03 Hoang NT , Takanori Maehara

Graph matching or quadratic assignment, is the problem of labeling the vertices of two graphs so that they are as similar as possible. A common method for approximately solving the NP-hard graph matching problem is relaxing it to a convex…

Optimization and Control · Mathematics 2017-05-23 Nadav Dym

The graph isomorphism (GI) problem, which asks whether two graphs are structurally identical, occupies a unique position in computational complexity -- it is neither known to be solvable in polynomial time, nor proven to be NP-complete. We…

Optimization and Control · Mathematics 2026-05-21 Wenjie Xiao , Mathieu Besançon , Patrick Gelß , Deborah Hendrych , Stefan Klus , Sebastian Pokutta

A commonly studied means of parameterizing graph problems is the deletion distance from triviality (Guo et al. 2004), which counts vertices that need to be deleted from a graph to place it in some class for which efficient algorithms are…

Data Structures and Algorithms · Computer Science 2014-10-17 Jannis Bulian , Anuj Dawar

Graph Isomorphism is the prime example of a computational problem with a wide difference between the best known lower and upper bounds on its complexity. We bridge this gap for a natural and important special case, planar graph isomorphism,…

Computational Complexity · Computer Science 2009-01-30 Samir Datta , Nutan Limaye , Prajakta Nimbhorkar , Thomas Thierauf , Fabian Wagner

In this paper we study the problem of testing graph isomorphism (GI) in the CONGEST distributed model. In this setting we test whether the distributive network, $G_U$, is isomorphic to $G_K$ which is given as an input to all the nodes in…

Data Structures and Algorithms · Computer Science 2020-03-03 Reut Levi , Moti Medina

This paper presents the novel `uniqueness tree' algorithm, as one possible method for determining whether two finite, undirected graphs are isomorphic. We prove that the algorithm has polynomial time complexity in the worst case, and that…

Discrete Mathematics · Computer Science 2016-06-22 Jonathan Gorard

Graphs are versatile tools for representing structured data. As a result, a variety of machine learning methods have been studied for graph data analysis. Although many such learning methods depend on the measurement of differences between…

Machine Learning · Statistics 2021-06-18 Tomoki Yoshida , Ichiro Takeuchi , Masayuki Karasuyama