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Related papers: Limit theorems for exponential random graphs

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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 self-loops and multiple edges in the configuration model as the size of the graph tends to infinity. The interest in these random variables is due to the fact that the configuration model, conditioned on being simple, is a…

Probability · Mathematics 2017-02-06 Omer Angel , Remco van der Hofstad , Cecilia Holmgren

We study the behavior of exponential random graphs in both the sparse and the dense regime. We show that exponential random graphs are approximate mixtures of graphs with independent edges whose probability matrices are critical points of…

Probability · Mathematics 2018-04-20 Ronen Eldan , Renan Gross

Based on numerical simulation and local stability analysis we describe the structure of the phase space of the edge/triangle model of random graphs. We support simulation evidence with mathematical proof of continuity and discontinuity for…

Combinatorics · Mathematics 2017-10-25 Richard Kenyon , Charles Radin , Kui Ren , Lorenzo Sadun

We introduce the Density Formula for (topological) drawings of graphs in the plane or on the sphere, which relates the number of edges, vertices, crossings, and sizes of cells in the drawing. We demonstrate its capability by providing…

In this paper we prove a quantiative local limit theorem for the distribution of the number of triangles in the Erd\H{o}s-Renyi random graph $G(n,p)$, for a fixed $p\in (0,1)$. This proof is an extension of the previous work of Gilmer and…

Combinatorics · Mathematics 2017-03-22 Ross Berkowitz

In the random geometric graph $G(n,r_n)$, $n$ vertices are placed randomly in Euclidean $d$-space and edges are added between any pair of vertices distant at most $r_n$ from each other. We establish strong laws of large numbers (LLNs) for a…

Probability · Mathematics 2020-06-29 Dieter Mitsche , Mathew D. Penrose

In this paper, we study the task of detecting the edge dependency between two weighted random graphs. We formulate this task as a simple hypothesis testing problem, where under the null hypothesis, the two observed graphs are statistically…

Machine Learning · Computer Science 2024-09-25 Mor Oren , Vered Paslev , Wasim Huleihel

We consider the problem of estimating the parameters in a pairwise graphical model in which the distribution of each node, conditioned on the others, may have a different parametric form. In particular, we assume that each node's…

Methodology · Statistics 2014-08-05 Shizhe Chen , Daniela Witten , Ali Shojaie

Given $\alpha \in (0, \infty)$ and $r \in (0, \infty)$, let ${\cal D}_{r, \alpha}$ be the disc of radius $r$ in the hyperbolic plane having curvature $-\alpha^2$. Consider the Poisson point process having uniform intensity density on ${\cal…

Probability · Mathematics 2021-01-01 Nikolaos Fountoulakis , Joseph Yukich

Elek and Lippner (2010) showed that the convergence of a sequence of bounded-degree graphs implies the existence of a limit for the proportion of vertices covered by a maximum matching. We provide a characterization of the limiting…

Probability · Mathematics 2012-04-12 Charles Bordenave , Marc Lelarge , Justin Salez

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

We study vectors chosen at random from a compact convex polytope in $\mathbb{R}^n$ given by a finite number of linear constraints. We determine which projections of these random vectors are asymptotically normal as $n\to\infty$. Marginal…

Probability · Mathematics 2025-03-18 Fabrice Gamboa , Martin Venker

This paper investigates properties of the class of graphs based on exchangeable point processes. We provide asymptotic expressions for the number of edges, number of nodes and degree distributions, identifying four regimes: (i) a dense…

Statistics Theory · Mathematics 2025-02-06 François Caron , Francesca Panero , Judith Rousseau

The exponential family of random graphs has been a topic of continued research interest. Despite the relative simplicity, these models capture a variety of interesting features displayed by large-scale networks and allow us to better…

Statistical Mechanics · Physics 2016-06-10 Mei Yin

Desirable random graph models (RGMs) should (i) reproduce common patterns in real-world graphs (e.g., power-law degrees, small diameters, and high clustering), (ii) generate variable (i.e., not overly similar) graphs, and (iii) remain…

Machine Learning · Computer Science 2025-09-26 Fanchen Bu , Ruochen Yang , Paul Bogdan , Kijung Shin

We give the first polynomial-time, differentially node-private, and robust algorithm for estimating the edge density of Erd\H{o}s-R\'enyi random graphs and their generalization, inhomogeneous random graphs. We further prove…

Data Structures and Algorithms · Computer Science 2024-06-05 Hongjie Chen , Jingqiu Ding , Yiding Hua , David Steurer

In this paper we consider the Erd\H{o}s-R\'enyi random graph in the sparse regime in the limit as the number of vertices $n$ tends to infinity. We are interested in what this graph looks like when it contains many triangles, in two…

Probability · Mathematics 2026-01-27 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

We introduce a model for a growing random graph based on simultaneous reproduction of the vertices. The model can be thought of as a generalisation of the reproducing graphs of Southwell and Cannings and Bonato et al to allow for a random…

Probability · Mathematics 2011-04-20 Jonathan Jordan

The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of…

Data Structures and Algorithms · Computer Science 2017-10-30 Duru Türkoğlu , Ata Turk