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In the last twenty years network science has proven its strength in modelling many real-world interacting systems as generic agents, the nodes, connected by pairwise edges. Yet, in many relevant cases, interactions are not pairwise but…

Physics and Society · Physics 2020-02-26 Timoteo Carletti , Federico Battiston , Giulia Cencetti , Duccio Fanelli

This paper investigates the addition of random edges to arbitrary dense graphs; in particular, we determine the number of random edges required to ensure various monotone properties including the appearance of a fixed size clique, small…

Combinatorics · Mathematics 2016-05-25 Tom Bohman , Alan Frieze , Michael Krivelevich , Ryan R. Martin

We present a novel approach to study the evolution of the size (i.e. the number of vertices) of the giant component of a random graph process. It is based on the exploration algorithm called simultaneous breadth-first walk, introduced by…

Probability · Mathematics 2025-07-17 Josué Corujo , Sophie Lemaire , Vlada Limic

Coalescing random walk on a unimodular random rooted graph for which the root has finite expected degree visits each site infinitely often almost surely. A corollary is that an opinion in the voter model on such graphs has infinite expected…

Probability · Mathematics 2018-04-06 Eric Foxall , Tom Hutchcroft , Matthew Junge

We consider a random object that is associated with both random walks and random media, specifically, the superposition of a configuration of subcritical Bernoulli percolation on an infinite connected graph and the trace of the simple…

Probability · Mathematics 2019-09-10 Kazuki Okamura

Graphlets are induced subgraph patterns that are crucial to the understanding of the structure and function of a large network. A lot of efforts have been devoted to calculating graphlet statistics where random walk based approaches are…

Social and Information Networks · Computer Science 2020-05-12 Simiao Jiao , Zihui Xue , Xiaowei Chen , Yuedong Xu

Kernel and linear regression have been recently explored in the prediction of graph signals as the output, given arbitrary input signals that are agnostic to the graph. In many real-world problems, the graph expands over time as new nodes…

Machine Learning · Computer Science 2019-11-27 Arun Venkitaraman , Saikat Chatterjee , Bo Wahlberg

Many real-world problems are naturally modeled as heterogeneous graphs, where nodes and edges represent multiple types of entities and relations. Existing learning models for heterogeneous graph representation usually depend on the…

In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between…

Probability · Mathematics 2023-07-10 Caio Alves , Rodrigo Ribeiro , Rémy Sanchis

We prove almost sure convergence of the maximum degree in an evolving graph model combining a growing number of local choices with sublinear preferential attachment. At each step in the growth of the graph, a new vertex is introduced. Then…

Probability · Mathematics 2019-11-19 Yury Malyshkin

We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it is either duplicated or its edges are deleted. Duplication has a given probability. We analyse the limit distribution of the degree of a…

Probability · Mathematics 2014-09-19 Ágnes Backhausz , Tamás F. Móri

Consider the complete n-vertex graph whose edge-lengths are independent exponentially distributed random variables. Simultaneously for each pair of vertices, put a constant flow between them along the shortest path. Each edge gets some…

Probability · Mathematics 2007-08-06 David J. Aldous , Shankar Bhamidi

In this work we consider temporal graphs, i.e. graphs, each edge of which is assigned a set of discrete time-labels drawn from a set of integers. The labels of an edge indicate the discrete moments in time at which the edge is available. We…

Data Structures and Algorithms · Computer Science 2013-10-30 Paul G. Spirakis , Eleni Ch. Akrida

Finding all maximal $k$-plexes on networks is a fundamental research problem in graph analysis due to many important applications, such as community detection, biological graph analysis, and so on. A $k$-plex is a subgraph in which every…

Data Structures and Algorithms · Computer Science 2022-05-03 Qiangqiang Dai , Rong-Hua Li , Hongchao Qin , Meihao Liao , Guoren Wang

We propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e. node) depends on both the current and previous states -- hence, lagged. The existing random walk sampling…

Statistics Theory · Mathematics 2022-05-16 Li-Chun Zhang

We define a general model of stochastically-evolving graphs, namely the \emph{Edge-Uniform Stochastically-Evolving Graphs}. In this model, each possible edge of an underlying general static graph evolves independently being either alive or…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-19 Ioannis Lamprou , Russell Martin , Paul Spirakis

We study some percolation problems on the complete graph over $\mathbf N$. In particular, we give sharp sufficient conditions for the existence of (finite or infinite) cliques and paths in a random subgraph. No specific assumption on the…

Probability · Mathematics 2011-03-29 A. Berarducci , P. Majer , M. Novaga

We consider the edge-triangle model, a two-parameter family of exponential random graphs in which dependence between edges is introduced through triangles. In the so-called replica symmetric regime, the limiting free energy exists together…

Probability · Mathematics 2023-01-31 Alessandra Bianchi , Francesca Collet , Elena Magnanini

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 a random graph in which vertices can have one of two possible colours. Each vertex switches its colour at a rate that is proportional to the number of vertices of the other colour to which it is connected by an edge. Each edge…

Probability · Mathematics 2026-04-21 Siva Athreya , Frank den Hollander , Adrian Röllin