Connectivity for random graphs from a weighted bridge-addable class by McDiarmid, C

“…There has been much recent interest in random graphs sampled uniformly from the n-vertex graphs in a suitable structured class, such as the class of all planar graphs. …”

Scaling laws for properties of random graphs that grow via successive combination by Grindrod, P

“…We discuss a further wide range of random graph combination operators to which this theory now applies, indicating the ubiquity of growth scaling laws (and asymptotic decay scaling laws) within applications, where the modules are quite distinct, yet may be considered as instances drawn from the same random graph. …”

Handwritten character recognition using a random graph model by relaxation matching / by 383643 Lieh, June-Rong

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Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints by Nicolò Vallarano, Matteo Bruno, Emiliano Marchese, Giuseppe Trapani, Fabio Saracco, Giulio Cimini, Mario Zanon, Tiziano Squartini

“…Abstract Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. …”
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Dynamic Random Graph Protection Scheme Based on Chaos and Cryptographic Random Mapping by Zhu Fang, Zhengquan Xu

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Exponential random graph model parameter estimation for very large directed networks. by Alex Stivala, Garry Robins, Alessandro Lomi

“…Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. …”
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Bounding Extremal Degrees of Edge-Independent Random Graphs Using Relative Entropy by Yilun Shang

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Central limit theorem for the principal eigenvalue and eigenvector of Chung–Lu random graphs by Pierfrancesco Dionigi, Diego Garlaschelli, Rajat Subhra Hazra, Frank den Hollander, Michel Mandjes

Subjects: “…Chung–Lu random graph…”
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Power-Law Random Graphs’ Robustness: Link Saving and Forest Fire Model by Marina Leri, Yury Pavlov

“…We consider random graphs with node degrees drawn independently from a power- law distribution. …”
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ergm 4: New Features for Analyzing Exponential-Family Random Graph Models by Pavel N. Krivitsky, David R. Hunter, Martina Morris, Chad Klumb

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Limit theorems for the weights and the degrees in anN-interactions random graph model by Fazekas István, Porvázsnyik Bettina

Subjects: “…random graph…”
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Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals by Philip Leifeld, Skyler J. Cranmer, Bruce A. Desmarais

Subjects: “…temporal exponential random graph model…”
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Exploring Coinvestment Partner Selection Strategies Using Exponential Random Graph Models by Jie Ren

“…This research analyzes cooperative relationships using exponential random graph models, considering both structural effects and node attributes. …”
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Modelling equilibration of local many-body quantum systems by random graph ensembles by Daniel Nickelsen, Michael Kastner

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Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets by Ackerman, Nate, Freer, Cameron E., Kaddar, Younesse, Karwowski, Jacek, Moss, Sean, Roy, Daniel, Staton, Sam, Yang, Hongseok

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Probabilistic programming interfaces for random graphs: Markov categories, graphons, and nominal sets by Ackerman, NL, Freer, CE, Kaddar, Y, Karwowski, J, Moss, SK, Roy, DM, Staton, S, Yang, H

Using latent variables to account for heterogeneity in exponential family random graph models by Koskinen, J

“…We consider relaxing the homogeneity assumption in exponential family random graph models (ERGMs) using binary latent class indicators. …”

A random graph theoretic framework for analyzing instantly decodable network codes by Etemadi Tajbakhsh, S, Sadeghi, P, Coon, J

“…We use some results from random graph theory and apply various relaxations to provide a closed form approximation of the average decoding delay. …”

Connectivity of Random Geometric Hypergraphs by Henry-Louis de Kergorlay, Desmond J. Higham

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Modeling heterogeneity in random graphs through latent space models: a selective review* by Matias Catherine, Robin Stéphane

“…We present a selective review on probabilistic modeling of heterogeneity in random graphs. We focus on latent space models and more particularly on stochastic block models and their extensions that have undergone major developments in the last five years.…”
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