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The treewidth of a graph is an important invariant in structural and algorithmic graph theory. This paper studies the treewidth of line graphs. We show that determining the treewidth of the line graph of a graph $G$ is equivalent to…

Combinatorics · Mathematics 2014-09-25 Daniel J. Harvey , David R. Wood

The processes of constructing some graphs from others using binary operations of union with intersection (gluing) are studied. For graph classes closed with respect to gluing operations the elemental and operational bases are introduced.…

Combinatorics · Mathematics 2020-11-24 M. A. Iordanski

Error-tolerant graph matching gathers an important family of problems. These problems aim at finding correspondences between two graphs while integrating an error model. In the Graph Edit Distance (GED) problem, the insertion/deletion of…

Discrete Mathematics · Computer Science 2021-04-19 Romain Raveaux

This paper will contribute to a practical problem, Urban Traffic. We will investigate those features, try to simplify the complexity and formulize this dynamic system. These contents mainly contain how to analyze a decision problem with…

Data Structures and Algorithms · Computer Science 2015-09-17 Yong Tan

We consider graphs with vertices of degree 1 or 2 and prove that the numbers of components of sizes 2 to q have a limit normal distribution for any q > 1. The result is also extended to multigraphs.

Combinatorics · Mathematics 2014-12-12 Nicolas Broutin , Élie de Panafieu

This paper addresses the problem of a boundary control design for traffic evolving in a large-scale urban network. The traffic state is described on a macroscopic scale and corresponds to the vehicle density, whose dynamics are governed by…

Optimization and Control · Mathematics 2021-03-17 Liudmila Tumash , Carlos Canudas-de-Wit , Maria Laura Delle Monache

We study the tailoring of structured random graph ensembles to real networks, with the objective of generating precise and practical mathematical tools for quantifying and comparing network topologies macroscopically, beyond the level of…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. Annibale , A. C. C. Coolen , L. P. Fernandes , F. Fraternali , J. Kleinjung

The aim of this paper is to obtain new inequalities for a large family of generalizations of the Wiener Index and to characterize the set of extremal graphs with respect to them. Our main results provide upper and lower bounds for these…

Combinatorics · Mathematics 2022-01-17 Álvaro Martínez-Pérez , osé M. Rodríguez

Networks are a powerful tool to model complex systems, and the definition of many Graph Neural Networks (GNN), Deep Learning algorithms that can handle networks, has opened a new way to approach many real-world problems that would be hardly…

Machine Learning · Computer Science 2021-09-28 Marco Grassia , Manlio De Domenico , Giuseppe Mangioni

In trying to generalize the classic Sylvester-Gallai theorem and De Bruijn-Erd\H{o}s theorem in plane geometry, lines and closure lines were previously defined for metric spaces and hypergraphs. Both definitions do not obey the geometric…

Metric Geometry · Mathematics 2014-02-25 Xiaomin Chen , Guangda Huzhang , Peihan Miao , Kuan Yang

In network tomography, one goal is to identify a small set of failed links in a network, by sending a few packets through the network and seeing which reach their destination. This problem can be seen as a variant of combinatorial group…

Information Theory · Computer Science 2018-09-12 Bruce Spang , Mary Wootters

Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph learning demonstrates strong performance and versatility…

Machine Learning · Computer Science 2025-12-23 Ahsan Shehzad , Feng Xia , Shagufta Abid , Ciyuan Peng , Shuo Yu , Dongyu Zhang , Karin Verspoor

Complex networks or graphs are ubiquitous in sciences and engineering: biological networks, brain networks, transportation networks, social networks, and the World Wide Web, to name a few. Spectral graph theory provides a set of useful…

Statistics Theory · Mathematics 2019-01-23 Subhadeep Mukhopadhyay , Kaijun Wang

In this paper, we present a survey of the use of graph theoretical techniques in Biology. In particular, we discuss recent work on identifying and modelling the structure of bio-molecular networks, as well as the application of centrality…

Molecular Networks · Quantitative Biology 2007-05-23 Oliver Mason , Mark Verwoerd

This tutorial paper refers to the use of graph-theoretic concepts for analyzing brain signals. For didactic purposes it splits into two parts: theory and application. In the first part, we commence by introducing some basic elements from…

Neurons and Cognition · Quantitative Biology 2020-07-14 Nikolaos Laskaris , Dimitrios A. Adamos , Anastasios Bezerianos

We define and study structural properties of hypergraphs of models of a theory including lattice ones. Characterizations for the lattice properties of hypergraphs of models of a theory, as well as for structures on sets of isomorphism types…

Logic · Mathematics 2018-02-28 Beibut Kulpeshov , Sergey Sudoplatov

This work is devoted to the study of the relationships between graph theory and the qualitative analysis of ordinary differential equations, with a special focus on two-dimensional systems. In particular, we reinterpret classical results…

Dynamical Systems · Mathematics 2026-04-01 Marcos Masip

Vertex similarity is a major problem in network science with a wide range of applications. In this work we provide novel perspectives on finding (dis)similar vertices within a network and across two networks with the same number of vertices…

Social and Information Networks · Computer Science 2013-05-28 Charalampos E. Tsourakakis

We characterise the form of all simple, finite graphs for which the girth of the graph is equal to the circumference of the graph. We apply this to prove a bound on the number of edges in such a graph.

Combinatorics · Mathematics 2022-10-11 Lewis Stanton , Jeffrey Thompson

The principal innovative idea in this paper is to transform the original complex nonlinear modeling problem into a combination of linear problem and very simple nonlinear problems. The key step is the generalized linearization of nonlinear…

Computational Engineering, Finance, and Science · Computer Science 2024-09-21 W. Chen