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Given a time series of graphs G(t) = (V, E(t)), t = 1, 2, ..., where the fixed vertex set V represents "actors" and an edge between vertex u and vertex v at time t (uv \in E(t)) represents the existence of a communications event between…

Machine Learning · Statistics 2015-06-11 Youngser Park , Carey E. Priebe , Abdou Youssef

Graph colouring is a combinatorial optimisation problem with applications in several important domains, including sports scheduling, cartography, street map navigation, and timetabling. It is also of significant theoretical interest and a…

History and Overview · Mathematics 2026-02-23 Rhyd Lewis

A unit disk graph is the intersection graph of disks of equal radii in the plane. The class of unit disk graphs is hereditary, and therefore admits a characterization in terms of minimal forbidden induced subgraphs. In spite of quite active…

Combinatorics · Mathematics 2016-02-29 Aistis Atminas , Viktor Zamaraev

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

A new alternative method to approximate the Visibility Graph (VG) of a time series has been introduced here. It exploits the fact that most of the nodes in the resulting network are not connected to those that are far away from them. This…

Data Analysis, Statistics and Probability · Physics 2023-11-20 R. Carmona-Cabezas , J. Gomez-Gomez , E. Gutierrez de Rave , F. J. Jimenez-Hornero

For a graph $G$, a function $\psi$ is called a \emph{bar visibility representation} of $G$ when for each vertex $v \in V(G)$, $\psi(v)$ is a horizontal line segment (\emph{bar}) and $uv \in E(G)$ iff there is an unobstructed, vertical,…

Computational Geometry · Computer Science 2021-12-17 Steven Chaplick , Grzegorz Guśpiel , Grzegorz Gutowski , Tomasz Krawczyk , Giuseppe Liotta

Graph Neural Networks (GNNs) have paved the way for being a cornerstone in graph-related learning tasks. Yet, the ability of GNNs to capture structural interactions within graphs remains under-explored. In this work, we address this gap by…

Machine Learning · Computer Science 2025-03-04 Asela Hevapathige , Qing Wang

Given a directed graph D = (V,A) we define its intersection graph I(D) = (A,E) to be the graph having A as a node-set and two nodes of I(D) are adjacent if their corresponding arcs share a common node that is the tail of at least one of…

Combinatorics · Mathematics 2013-06-19 Mourad Baïou , Laurent Beaudou , Zhentao Li , Vincent Limouzy

A graph $G$ is a $B_0$-VPG graph if one can associate a path on a rectangular grid with each vertex such that two vertices are adjacent if and only if the corresponding paths intersect at at least one grid-point. A graph $G$ is a contact…

In this paper we introduce a graph structure, called subspace sum graph $\mathcal{G}(\mathbb{V})$ on a finite dimensional vector space $\mathbb{V}$ where the vertex set is the collection of non-trivial proper subspaces of a vector space and…

Combinatorics · Mathematics 2017-02-28 Angsuman Das

Graph Neural Networks (GNNs) have become a standard approach for learning from graph-structured data. However, their reliance on parametric classifiers (most often linear softmax layers) limits interpretability and sometimes hinders…

Machine Learning · Computer Science 2026-02-03 Zeljko Bolevic , Milos Brajovic , Isidora Stankovic , Ljubisa Stankovic

Recently, a set of graph-based tools have been introduced for the identification of singular events of O3, NO2 and temperature time series, as well as description of their dynamics. These are based on the use of the Visibility Graphs (VG).…

Atmospheric and Oceanic Physics · Physics 2023-11-21 R. Carmona-Cabezas , J. Gomez-Gomez , E. Gutierrez de Rave , E. Sanchez-Lopez , J. Serrano , F. J. Jimenez-Hornero

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

Mapping complex input data into suitable lower dimensional manifolds is a common procedure in machine learning. This step is beneficial mainly for two reasons: (1) it reduces the data dimensionality and (2) it provides a new data…

Machine Learning · Computer Science 2018-11-28 Daniele Zambon , Lorenzo Livi , Cesare Alippi

Unigraphs are graphs identifiable up to isomorphism from their degree sequences. Given a class $\mathcal{A}$ of graphs, we define the class of $\mathcal{A}$-unigraphs to be graphs identifiable from degree sequence and membership in…

Combinatorics · Mathematics 2024-06-07 R. Whitman

Let $\langle G_r,G_b \rangle$ be a pair of plane $st$-graphs with the same vertex set $V$. A simultaneous visibility representation with L-shapes of $\langle G_r,G_b \rangle$ is a pair of bar visibility representations…

Computational Geometry · Computer Science 2019-09-04 William S. Evans , Giuseppe Liotta , Fabrizio Montecchiani

In this paper we consider Contact graphs of Paths on a Grid (CPG graphs), i.e. graphs for which there exists a family of interiorly disjoint paths on a grid in one-to-one correspondence with their vertex set such that two vertices are…

Computational Geometry · Computer Science 2018-09-07 Zakir Deniz , Esther Galby , Andrea Munaro , Bernard Ries

Obstacle representations of graphs have been investigated quite intensely over the last few years. We focus on graphs that can be represented by a single obstacle. Given a (topologically open) polygon $C$ and a finite set $P$ of points in…

Computational Geometry · Computer Science 2016-09-02 Steven Chaplick , Fabian Lipp , Ji-won Park , Alexander Wolff

Since the introduction of the Hermitian adjacency matrix for digraphs, interest in so-called complex unit gain graphs has surged. In this work, we consider gain graphs whose spectra contain the minimum number of two distinct eigenvalues.…

Combinatorics · Mathematics 2021-05-20 Pepijn Wissing , Edwin R. van Dam

A geometric grid class consists of those permutations that can be drawn on a specified set of line segments of slope \pm1 arranged in a rectangular pattern governed by a matrix. Using a mixture of geometric and language theoretic methods,…

Combinatorics · Mathematics 2012-02-06 Michael H. Albert , M. D. Atkinson , Mathilde Bouvel , Nik Ruškuc , Vincent Vatter