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We study a family of directed random graphs whose arcs are sampled independently of each other, and are present in the graph with a probability that depends on the attributes of the vertices involved. In particular, this family of models…

Probability · Mathematics 2017-12-12 Junyu Cao , Mariana Olvera-Cravioto

There has been an explosion of interest in statistical models for analyzing network data, and considerable interest in the class of exponential random graph (ERG) models, especially in connection with difficulties in computing maximum…

Machine Learning · Statistics 2009-01-05 Stephen E. Fienberg , Alessandro Rinaldo , Yi Zhou

A growing random graph is constructed by successively sampling without replacement an element from the pool of virtual vertices and edges. At start of the process the pool contains $N$ virtual vertices and no edges. Each time a vertex is…

Probability · Mathematics 2024-02-29 Michael Farber , Alexander Gnedin , Wajid Mannan

We establish the conditions under which several algorithmically exploitable structural features hold for random intersection graphs, a natural model for many real-world networks where edges correspond to shared attributes. Specifically, we…

Social and Information Networks · Computer Science 2017-02-10 Matthew Farrell , Timothy Goodrich , Nathan Lemons , Felix Reidl , Fernando Sánchez Villaamil , Blair D. Sullivan

We consider two independent Erd\H{o}s-R\'enyi random graphs, with possibly different parameters, and study two isomorphism problems, a graph embedding problem and a common subgraph problem. Under certain conditions on the graph parameters…

Combinatorics · Mathematics 2025-06-25 Dimitris Diamantidis , Takis Konstantopoulos , Linglong Yuan

Scale-free networks contain many small cliques and cycles. We model such networks as inhomogeneous random graphs with regularly varying infinite-variance weights. For these models, the number of cliques and cycles have exact integral…

Probability · Mathematics 2019-03-27 A. J. E. M. Janssen , Johan S. H. van Leeuwaarden , Seva Shneer

Exponential-family random graph models (ERGMs) provide a principled and flexible way to model and simulate features common in social networks, such as propensities for homophily, mutuality, and friend-of-a-friend triad closure, through…

Methodology · Statistics 2012-08-01 Pavel N. Krivitsky

We study models of weighted exponential random graphs in the large network limit. These models have recently been proposed to model weighted network data arising from a host of applications including socio-econometric data such as migration…

Probability · Mathematics 2018-07-12 Shankar Bhamidi , Suman Chakraborty , Skyler Cranmer , Bruce Desmarais

A graph property is said to be elusive ( evasive) if every algorithm testing this property by asking questions of the form "is there an edge between vertices x and y" requires, in the worst case, to ask about all pairs of vertices. The…

Combinatorics · Mathematics 2022-06-22 Tamás Csernák , Lajos Soukup

We provide precise asymptotic estimates for the number of several classes of labelled cubic planar graphs, and we analyze properties of such random graphs under the uniform distribution. This model was first analyzed by Bodirsky et al.…

Combinatorics · Mathematics 2019-07-26 Marc Noy , Clément Requilé , Juanjo Rué

For any positive edge density $p$, a random graph in the Erd\H{o}s-Renyi $G_{n,p}$ model is connected with non-zero probability, since all edges are mutually independent. We consider random graph models in which edges that do not share…

Large graphs are sometimes studied through their degree sequences (power law or regular graphs). We study graphs that are uniformly chosen with a given degree sequence. Under mild conditions, it is shown that sequences of such graphs have…

Probability · Mathematics 2011-08-31 Sourav Chatterjee , Persi Diaconis , Allan Sly

Inspired by the prospect of having discretized spaces emerge from random graphs, we construct a collection of simple and explicit exponential random graph models that enjoy, in an appropriate parameter regime, a roughly constant vertex…

Disordered Systems and Neural Networks · Physics 2021-10-01 Pawat Akara-pipattana , Thiparat Chotibut , Oleg Evnin

A significant generalization of the Erd\"os-R\'enyi random graph model is an `inhomogeneous' random graph where the edge probabilities vary according to vertex types. We identify the threshold value for this random graph with a finite…

Probability · Mathematics 2024-11-06 Hamin Jung

We numerically investigate typical graphs in a region of the Strauss model of random graphs with constraints on the densities of edges and triangles. This region, where typical graphs had been expected to be bipodal but turned out to be…

Combinatorics · Mathematics 2025-08-26 William DiCarlo , Lorenzo Sadun

The classical random matrix theory is mostly focused on asymptotic spectral properties of random matrices as their dimensions grow to infinity. At the same time many recent applications from convex geometry to functional analysis to…

Functional Analysis · Mathematics 2014-03-05 Mark Rudelson , Roman Vershynin

We consider a class of growing random graphs obtained by creating vertices sequentially one by one: at each step, we choose uniformly the neighbours of the newly created vertex; its degree is a random variable with a fixed but arbitrary…

Combinatorics · Mathematics 2013-11-13 Svante Janson , Simone Severini

In this paper we introduce the perturbed version of the Barab\'asi-Albert random graph with multiple type edges and prove the existence of the (generalized) asymptotic degree distribution. Similarly to the non-perturbed case, the asymptotic…

Probability · Mathematics 2019-09-19 Ágnes Backhausz , Bence Rozner

Exponential random graph models have attracted significant research attention over the past decades. These models are maximum-entropy ensembles under the constraints that the expected values of a set of graph observables are equal to given…

Statistics Theory · Mathematics 2015-10-30 Konstantin Zuev , Or Eisenberg , Dmitri Krioukov

We study a random graph model in continuous time. Each vertex is partially copied with the same rate, i.e.\ an existing vertex is copied and every edge leading to the copied vertex is copied with independent probability $p$. In addition,…

Probability · Mathematics 2024-07-02 Felix Hermann , Peter Pfaffelhuber
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