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Related papers: Shattering, Graph Orientations, and Connectivity

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In this note we elaborate on some notions of surface area for discrete graphs which are closely related to the inverse degree. These notions then naturally lead to associated connectivity measures of graphs and to the definition of a…

Combinatorics · Mathematics 2026-03-09 Patrizio Bifulco , Joachim Kerner

A set $V$ is said to be separated by subsets $V_1,\ldots,V_k$ if, for every pair of distinct elements of $V$, there is a set $V_i$ that contains exactly one of them. Imposing structural constraints on the separating subsets is often…

Combinatorics · Mathematics 2024-08-06 Lyuben Lichev , Nicolás Sanhueza-Matamala

Similarity notions between vertices in a graph, such as structural and regular equivalence, are one of the main ingredients in clustering tools in complex network science. We generalise structural and regular equivalences for undirected…

Combinatorics · Mathematics 2026-01-01 Marzieh Eidi , Nina Otter

In this paper, we propose a new type of graph, denoted as "embedded-graph", and its theory, which employs a distributed representation to describe the relations on the graph edges. Embedded-graphs can express linguistic and complicated…

Discrete Mathematics · Computer Science 2017-09-15 Atsushi Yokoyama

We develop a theory to measure the variance and covariance of probability distributions defined on the nodes of a graph, which takes into account the distance between nodes. Our approach generalizes the usual (co)variance to the setting of…

Physics and Society · Physics 2021-08-19 Karel Devriendt , Samuel Martin-Gutierrez , Renaud Lambiotte

Graph is an abstract representation commonly used to model networked systems and structure. In problems across various fields, including computer vision and pattern recognition, and neuroscience, graphs are often brought into comparison (a…

Optimization and Control · Mathematics 2022-03-04 Quoc Van Tran , Hyo-Sung Ahn

We study the statistical properties of the scattering matrix associated with generic quantum graphs. The scattering matrix is the quantum analogue of the classical evolution operator on the graph. For the energy-averaged spectral form…

Chaotic Dynamics · Physics 2009-10-31 Tsampikos Kottos , Holger Schanz

The eccentricity of a vertex $v$ in a graph $G$ is the maximum distance between $v$ and any other vertex of $G$. The diameter of a graph $G$ is the maximum eccentricity of a vertex in $G$. The eccentric connectivity index of a connected…

Discrete Mathematics · Computer Science 2024-03-11 Pierre Hauweele , Alain Hertz , Hadrien Mélot , Bernard Ries , Gauvain Devillez

In this paper we develop a structure called Link Algebra, in which we present a Set with two binary operations and an axiom system developed from the study of graph theory and set/antiset theory, sowing main theorems and definitions. Once…

Rings and Algebras · Mathematics 2011-03-22 Alfonso Bustamante

Graph and network visualization supports exploration, analysis and communication of relational data arising in many domains: from biological and social networks, to transportation and powergrid systems. With the arrival of AI-based…

We derive a number of upper and lower bounds for the first nontrivial eigenvalue of a finite quantum graph in terms of the edge connectivity of the graph, i.e., the minimal number of edges which need to be removed to make the graph…

Spectral Theory · Mathematics 2019-06-04 Gregory Berkolaiko , James B. Kennedy , Pavel Kurasov , Delio Mugnolo

Building upon [1], this study aims to introduce fractal geometry into graph theory, and to establish a potential theoretical foundation for complex networks. Specifically, we employ the method of substitution to create and explore…

Dynamical Systems · Mathematics 2024-05-29 Nero Ziyu Li

We consider graphs made of one-dimensional wires connected at vertices, and on which may live a scalar potential. We are interested in a scattering situation where such a network is connected to infinite leads. We study the correlations of…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Christophe Texier , Pascal Degiovanni

A well-defined distance on the parameter space is key to evaluating estimators, ensuring consistency, and building confidence sets. While there are typically standard distances to adopt in a continuous space, this is not the case for…

Statistics Theory · Mathematics 2026-02-02 Armeen Taeb , F. Richard Guo , Leonard Henckel

Steinerberger proposed a notion of curvature on graphs involving the graph distance matrix (J. Graph Theory, 2023). We show that nonnegative curvature is almost preserved under three graph operations. We characterize the distance matrix and…

Combinatorics · Mathematics 2025-05-06 Wei-Chia Chen , Mao-Pei Tsui

Vertex connectivity and edge connectivity are fundamental concepts in graph theory that have been widely studied from both structural and algorithmic perspectives. The focus of this paper is on computing these two parameters for graphs…

Data Structures and Algorithms · Computer Science 2025-10-14 Therese Biedl , Prosenjit Bose , Karthik Murali

We say that a set system $\mathcal{F}\subseteq 2^{[n]}$ shatters a given set $S\subseteq [n]$ if $2^S={F \cap S : F \in \mathcal{F}}$. The Sauer inequality states that in general, a set system $\mathcal{F}$ shatters at least $|\mathcal{F}|$…

Combinatorics · Mathematics 2012-11-06 Tamás Mészáros , Lajos Rónyai

We propose a model of optimal parallel transport between vector fields on a connection graph, which consists of a weighted graph along with a map from its edges to an orthogonal group. Inspired by the well-known equivalence of 1-Wasserstein…

Optimization and Control · Mathematics 2025-03-18 Sawyer Robertson , Dhruv Kohli , Gal Mishne , Alexander Cloninger

We discuss a link between graph theory and geometry that arises when considering graph dynamical systems with odd interactions. The equilibrium set in such systems is not a collection of isolated points, but rather a union of manifolds,…

Dynamical Systems · Mathematics 2024-08-28 Davide Sclosa

Most graph kernels are an instance of the class of $\mathcal{R}$-Convolution kernels, which measure the similarity of objects by comparing their substructures. Despite their empirical success, most graph kernels use a naive aggregation of…

Machine Learning · Computer Science 2019-10-31 Matteo Togninalli , Elisabetta Ghisu , Felipe Llinares-López , Bastian Rieck , Karsten Borgwardt