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Detecting anomalies in a temporal sequence of graphs can be applied is areas such as the detection of accidents in transport networks and cyber attacks in computer networks. Existing methods for detecting abnormal graphs can suffer from…

Machine Learning · Computer Science 2025-02-03 Sevvandi Kandanaarachchi , Conrad Sanderson , Rob J. Hyndman

We study the relation between the growth rate of a graph property and the entropy of the graph limits that arise from graphs with that property. In particular, for hereditary classes we obtain a new description of the colouring number,…

Combinatorics · Mathematics 2013-12-20 Hamed Hatami , Svante Janson , Balázs Szegedy

We consider the statistics of extreme eigenvalues of random $d$-regular graphs, with $N^{\mathfrak c}\leq d\leq N^{1/3-{\mathfrak c}}$ for arbitrarily small ${\mathfrak c}>0$. We prove that in this regime, the fluctuations of extreme…

Probability · Mathematics 2023-06-12 Jiaoyang Huang , Horng-Tzer Yau

Extremal graph theory studies the maximum or minimum number of subgraphs isomorphic to a prescribed graph under given constraints. \textit{Localization} has recently emerged as a framework that refines such problems by assigning extremal…

Combinatorics · Mathematics 2026-03-10 Rajat Adak , L. Sunil Chandran

We study thresholds for extremal properties of random discrete structures. We determine the threshold for Szemer\'edi's theorem on arithmetic progressions in random subsets of the integers and its multidimensional extensions and we…

Combinatorics · Mathematics 2016-09-20 Mathias Schacht

In this paper, we obtain a precise estimate of the probability that the sparse binomial random graph contains a large number of vertices in a triangle. The estimate of log of this probability is correct up to second order, and enables us to…

Probability · Mathematics 2025-08-21 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

Exponential-family random graph models (ERGMs) provide a principled way to model and simulate features common in human social networks, such as propensities for homophily and friend-of-a-friend triad closure. We show that, without…

Methodology · Statistics 2012-01-09 Pavel N. Krivitsky , Mark S. Handcock , Martina Morris

A zero-one matrix $M$ is said to contain another zero-one matrix $A$ if we can delete some rows and columns of $M$ and replace some $1$-entries with $0$-entries such that the resulting matrix is $A$. The extremal number of $A$, denoted…

Combinatorics · Mathematics 2024-03-08 Barnabás Janzer , Oliver Janzer , Van Magnan , Abhishek Methuku

We investigate symmetric edge polytopes generated by Erd\H{o}s--R\'enyi random graphs in a high-dimensional regime. These objects provide a natural and largely unexplored model of random lattice polytopes, in which geometric properties are…

Combinatorics · Mathematics 2026-03-12 Torben Donzelmann , Martina Juhnke , Benedikt Rednoß , Christoph Thäle

We find new upper bounds on the size of a minimum totally dominating set for random regular graphs and for regular graphs with large girth. These bounds are obtained through the analysis of a local algorithm using a method due to Hoppen and…

Combinatorics · Mathematics 2020-01-07 Carlos Hoppen , Giovane Mansan

We study topological properties of random closed curves on an orientable surface $S$ of negative Euler characteristic. Letting $\gamma_{n}$ denote the conjugacy class of the $n^{th}$ step of a simple random walk on the Cayley graph driven…

Geometric Topology · Mathematics 2022-11-17 Tarik Aougab , Jonah Gaster

A tight $\ell$-cycle minus an edge $C_\ell^-$ is the $3$-graph on the vertex set $[\ell]$, where any three consecutive vertices in the string $123\ldots\ell 1$ form an edge. We show that for every $\ell\ge 5$, $\ell$ not divisible by $3$,…

Combinatorics · Mathematics 2024-11-27 Bernard Lidicky , Connor Mattes , Florian Pfender

Graph convolutional networks (GCNs) are a widely used method for graph representation learning. To elucidate the capabilities and limitations of GCNs, we investigate their power, as a function of their number of layers, to distinguish…

Machine Learning · Statistics 2020-05-14 Abram Magner , Mayank Baranwal , Alfred O. Hero

Consider a random graph process where vertices are chosen from the interval $[0,1]$, and edges are chosen independently at random, but so that, for a given vertex $x$, the probability that there is an edge to a vertex $y$ decreases as the…

We consider a natural model of inhomogeneous random graphs that extends the classical Erd\H os-R\'enyi graphs and shares a close connection with the multiplicative coalescence, as pointed out by Aldous [AOP 1997]. In this model, the…

Probability · Mathematics 2020-02-10 Nicolas Broutin , Thomas Duquesne , Minmin Wang

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph ensemble with exponentially decaying random disconnection probabilities determined by an i.i.d. field of variables with heavy tails and infinite mean associated to the vertices of…

Probability · Mathematics 2026-04-01 Luca Avena , Diego Garlaschelli , Rajat Subhra Hazra , Margherita Lalli

The classic extremal problem is that of computing the maximum number of edges in an $F$-free graph. In the case where $F=K_{r+1}$, the extremal number was determined by Tur\'an. Later results, known as supersaturation theorems, proved that…

Combinatorics · Mathematics 2024-09-24 Jonathan Cutler , JD Nir , A. J. Radcliffe

In this paper we study the the average order of dominating sets in a graph, $\operatorname{avd}(G)$. Like other average graph parameters, the extremal graphs are of interest. Beaton and Brown (2021) conjectured that for all graphs $G$ of…

Combinatorics · Mathematics 2022-11-15 Iain Beaton , Ben Cameron

In this paper we investigate the extremal relationship between two well-studied graph parameters: the order of the largest homogeneous set in a graph $G$ and the maximal number of distinct degrees appearing in an induced subgraph of $G$,…

Combinatorics · Mathematics 2022-12-01 Eoin Long , Laurentiu Ploscaru

We investigate an extremal dynamics model of evolution with a variable number of units. Due to addition and removal of the units, the topology of the network evolves and the network splits into several clusters. The activity is mostly…

Statistical Mechanics · Physics 2009-10-31 Frantisek Slanina , Miroslav Kotrla