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The concept of the integrated adjacency matrix for mixed graphs was first introduced in [9], where its spectral properties were analyzed in relation to the structural characteristics of the mixed graph. Building upon this foundation, this…

Combinatorics · Mathematics 2025-07-08 G. Kalaivani , R. Rajkumar

A generalization of metric space is presented which is shown to admit a theory strongly related to that of ordinary metric spaces. To avoid the topological effects related to dropping any of the axioms of metric space, first a new, and…

Metric Geometry · Mathematics 2012-01-20 Ittay Weiss

In this paper, we consider a certain convolutional Laplacian for metric measure spaces and investigate its potential for the statistical analysis of complex objects. The spectrum of that Laplacian serves as a signature of the space under…

Statistics Theory · Mathematics 2022-04-14 Gilles Mordant , Axel Munk

We consider isomorphism properties of infinite random geometric graphs defined over a variety of metrics. In previous work, it was shown that for $\mathbb{R}^n$ with the $L_{\infty}$-metric, the infinite random geometric graph is, with…

Combinatorics · Mathematics 2014-08-12 Anthony Bonato , Jeannette Janssen

An obstacle representation of a graph is a mapping of the vertices onto points in the plane and a set of connected regions of the plane (called obstacles) such that the straight-line segment connecting the points corresponding to two…

We provide upper bounds on the perturbation of invariant subspaces of normal matrices measured using a metric on the space of vector subspaces of $\mathbb{C}^n$ in terms of the spectrum of both the unperturbed \& perturbed matrices, as well…

Spectral Theory · Mathematics 2021-06-22 Subhrajit Bhattacharya

In this work, we study the computability of topological graphs, which are obtained by gluing arcs and rays together at their endpoints. We prove that every semicomputable graph in a computable metric space can be approximated, with…

Logic in Computer Science · Computer Science 2026-04-15 Vedran Čačić , Matea Čelar , Marko Horvat , Zvonko Iljazović

In this paper, we study the graph isomorphism and graph automorphism problems. We propose a novel technique to analyze graph isomorphism and graph automorphism. Further we handled some strongly regular datasets for prove the efficiency of…

Combinatorics · Mathematics 2019-06-19 Sivakumar Karunakaran , Lavanya Selvaganesh

We study characteristics which might distinguish two-graphs by introducing different numerical measures on the collection of graphs on $n$ vertices. Two conjectures are stated, one using these numerical measures and the other using the deck…

Combinatorics · Mathematics 2008-10-20 David M. Duncan , Thomas R. Hoffman , James P. Solazzo

We suggest a combinatorial classification of metric filtrations in measure spaces; a complete invariant of such a filtration is its combinatorial scheme, a measure on the space of hierarchies of the group~$\mathbb Z$. In turn, the notion of…

Dynamical Systems · Mathematics 2018-12-20 A. Vershik , P. Zatitskiy

Adjacency between two vertices in graphs or hypergraphs is a pairwise relationship. It is redefined in this article as 2-adjacency. In general hypergraphs, hyperedges hold for $n$-adic relationship. To keep the $n$-adic relationship the…

Discrete Mathematics · Computer Science 2018-05-31 Xavier Ouvrard , Jean-Marie Le Goff , Stéphane Marchand-Maillet

A growing set of on-line applications are generating data that can be viewed as very large collections of small, dense social graphs -- these range from sets of social groups, events, or collaboration projects to the vast collection of…

Social and Information Networks · Computer Science 2013-05-15 Johan Ugander , Lars Backstrom , Jon Kleinberg

We suggest a new method of describing invariant measures on Markov compacta and path spaces of graphs, and thus of describing characters of some groups and traces of AF-algebras. The method relies on properties of filtrations associated…

Representation Theory · Mathematics 2014-08-15 Anatoly Vershik

Measuring similarity between complex objects is a fundamental task in many scientific fields. When objects are represented as graphs, graph similarity/distance measures offer a powerful framework for quantifying structural resemblance.…

Combinatorics · Mathematics 2025-09-30 Matthias Dehmer , Izudin Redžepović , Niko Tratnik , Petra Žigert Pleteršek

We consider modified Laplacian matrices of graphs, obtained by adding the identity matrix to the Laplacian matrix $L_G$ of a graph $G$. This results in a positive definite matrix $\tilde{L}_G$. The inverse of $\tilde{L}_G$ is a doubly…

Combinatorics · Mathematics 2025-09-24 Enide Andrade , Geir Dahl

Network theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. In recent years great progress has been made by augmenting `traditional' network theory.…

Data Analysis, Statistics and Probability · Physics 2016-06-03 Dominik Traxl , Niklas Boers , Jürgen Kurths

This paper introduces a novel Laplacian matrix aiming to enable the construction of spectral convolutional networks and to extend the signal processing applications for directed graphs. Our proposal is inspired by a Haar-like transformation…

Machine Learning · Computer Science 2025-10-02 Theodor-Adrian Badea , Bogdan Dumitrescu

We consider the density matrices derived from combinatorial laplacian matrix of graphs. Specifically, the star-relevant graph, which means adding certain edges on peripheral vertices of star graph, is the focus of this paper. Initially, we…

Mathematical Physics · Physics 2015-09-18 Jian-Qiang Li , Xiu-Bo Chen , Yi-Xian Yang

A recent line of research has concentrated on exploring the links between analytic and combinatorial theories of submodularity, uncovering several key connections between them. In this context, Lov\'asz initiated the study of matroids from…

Combinatorics · Mathematics 2024-10-16 Kristóf Bérczi , Márton Borbényi , László Lovász , László Márton Tóth

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful…

Machine Learning · Computer Science 2016-02-23 Xiaowen Dong , Dorina Thanou , Pascal Frossard , Pierre Vandergheynst