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Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

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

Hyperbolic random graphs inherit many properties that are present in real-world networks. The hyperbolic geometry imposes a scale-free network with a strong clustering coefficient. Other properties like a giant component, the small world…

Data Structures and Algorithms · Computer Science 2025-02-14 Samuel Baguley , Yannic Maus , Janosch Ruff , George Skretas

The edge-degeneracy model is an exponential random graph model that uses the graph degeneracy, a measure of the graph's connection density, and number of edges in a graph as its sufficient statistics. We show this model is relatively…

Statistics Theory · Mathematics 2016-09-19 Nicolas Kim , Dane Wilburne , Sonja Petrović , Alessandro Rinaldo

We consider a random geometric hypergraph model based on an underlying bipartite graph. Nodes and hyperedges are sampled uniformly in a domain, and a node is assigned to those hyperedges that lie with a certain radius. From a modelling…

Probability · Mathematics 2023-09-19 Henry-Louis de Kergorlay , Desmond J. Higham

Random hypergraphs extend the classical notion of random graphs by allowing hyperedges to join more than two vertices, making them well-suited for modeling higher-order interactions in complex systems. Despite their broad applicability,…

Probability · Mathematics 2026-04-08 Yanna J. Kraakman , Clara Stegehuis

This research establishes that many real-world networks exhibit bounded expansion, a strong notion of structural sparsity, and demonstrates that it can be leveraged to design efficient algorithms for network analysis. We analyze several…

Social and Information Networks · Computer Science 2018-10-15 Erik D. Demaine , Felix Reidl , Peter Rossmanith , Fernando Sanchez Villaamil , Somnath Sikdar , Blair D. Sullivan

This article discusses random hypergraphs with varying hyperedge sizes, admitting large hyperedges with size tending to infinity, and heavy-tailed limiting hyperedge size distributions. The main result describes a threshold for the random…

Combinatorics · Mathematics 2024-06-11 Elmer Bergman , Lasse Leskelä

Random intersection graphs model networks with communities, assuming an underlying bipartite structure of groups and individuals, where these groups may overlap. Group memberships are generated through the bipartite configuration model.…

Probability · Mathematics 2026-01-14 Remco van der Hofstad , Julia Komjathy , Viktoria Vadon

We characterize some asymptotic properties of edge exchangeable random graphs in terms of the measure used to generate them. In particular, we give a necessary and sufficient condition for eventual forever connectedness, a sufficient…

Probability · Mathematics 2026-05-07 Edward Eriksson

The notions of bounded expansion and nowhere denseness not only offer robust and general definitions of uniform sparseness of graphs, they also describe the tractability boundary for several important algorithmic questions. In this paper we…

Discrete Mathematics · Computer Science 2019-09-25 Wojciech Nadara , Marcin Pilipczuk , Roman Rabinovich , Felix Reidl , Sebastian Siebertz

Conventionally used exponential random graphs cannot directly model weighted networks as the underlying probability space consists of simple graphs only. Since many substantively important networks are weighted, this limitation is…

Probability · Mathematics 2019-06-10 Ryan DeMuse , Danielle Larcomb , Mei Yin

The intricate relations between elements in natural and human-made systems sustain the complex processes that shape our world, forming multiscale networks of interactions. These networks can be represented as graphs composed of nodes…

Disordered Systems and Neural Networks · Physics 2026-03-20 M. Ángeles Serrano

Hyperbolicity is a property of a graph that may be viewed as being a "soft" version of a tree, and recent empirical and theoretical work has suggested that many graphs arising in Internet and related data applications have hyperbolic…

Social and Information Networks · Computer Science 2013-09-17 Wei Chen , Wenjie Fang , Guangda Hu , Michael W. Mahoney

Through detailed analysis of scores of publicly available data sets corresponding to a wide range of large-scale networks, from communication and road networks to various forms of social networks, we explore a little-studied geometric…

Physics and Society · Physics 2013-07-02 W. Sean Kennedy , Onuttom Narayan , Iraj Saniee

Random intersection graphs containing an underlying community structure are a popular choice for modelling real-world networks. Given the group memberships, the classical random intersection graph is obtained by connecting individuals when…

Probability · Mathematics 2023-08-31 Marta Milewska , Remco van der Hofstad , Bert Zwart

Networks representing many complex systems in nature and society share some common structural properties like heterogeneous degree distributions and strong clustering. Recent research on network geometry has shown that those real networks…

Physics and Society · Physics 2015-09-23 Rodrigo Aldecoa , Chiara Orsini , Dmitri Krioukov

We define the crossing graph of a given embedded graph (such as a road network) to be a graph with a vertex for each edge of the embedding, with two crossing graph vertices adjacent when the corresponding two edges of the embedding cross…

Data Structures and Algorithms · Computer Science 2017-09-20 David Eppstein , Siddharth Gupta

We study the connections between the notions of combinatorial discrepancy and graph degeneracy. In particular, we prove that the maximum discrepancy over all subgraphs $H$ of a graph $G$ of the neighborhood set system of $H$ is sandwiched…

Discrete Mathematics · Computer Science 2021-11-30 Mario Grobler , Yiting Jiang , Patrice Ossona de Mendez , Sebastian Siebertz , Alexandre Vigny

We study a recent model for edge exchangeable random graphs introduced by Crane and Dempsey; in particular we study asymptotic properties of the random simple graph obtained by merging multiple edges. We study a number of examples, and show…

Probability · Mathematics 2017-08-02 Svante Janson
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