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Related papers: Consensus and Voting on Large Graphs: An Applicati…

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We extend the concept of the law of a finite graph to graphings, which are, in general, infinite graphs whose vertices are equipped with the structure of a probability space. By doing this, we obtain a vast array of new unimodular measures.…

Combinatorics · Mathematics 2012-03-13 Igor Artemenko

Majority dynamics is a process on a simple, undirected graph $G$ with an initial Red/Blue color for every vertex of $G$. Each day, each vertex updates its color following the majority among its neighbors, using its previous color for…

Combinatorics · Mathematics 2025-03-11 Jeong Han Kim , BaoLinh Tran

We study the limit theory of large threshold graphs and apply this to a variety of models for random threshold graphs. The results give a nice set of examples for the emerging theory of graph limits.

Combinatorics · Mathematics 2009-08-19 Persi Diaconis , Susan Holmes , Svante Janson

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 study the voter model, under node and link update, and the related invasion process on a single strongly connected component of a directed network. We implement an analytical treatment in the thermodynamic limit using the heterogeneous…

Disordered Systems and Neural Networks · Physics 2011-07-06 M. Angeles Serrano , Konstantin Klemm , Federico Vazquez , Victor M. Eguiluz , Maxi San Miguel

Local convergence techniques have become a key methodology to study sparse random graphs. However, convergence of many random graph properties does not directly follow from local convergence. A notable, and important, such random graph…

Probability · Mathematics 2025-10-07 Remco van der Hofstad

We consider a Random Graph Model on $\mathbb{Z}^{d}$ that incorporates the interplay between the statistics of the graph and the underlying space where the vertices are located. Based on a graphical construction of the model as the…

Statistics Theory · Mathematics 2024-06-19 Andressa Cerqueira , Nancy L. Garcia

In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a…

Machine Learning · Computer Science 2019-10-01 Zhiwei Deng , Megha Nawhal , Lili Meng , Greg Mori

The voter model consists of a set of agents whose opinion is a binary variable. At each time step, an agent along with a social neighbor is selected and the agent imitates the social neighbor at the next time step. In this paper, we study a…

Probability · Mathematics 2023-07-06 Hsin-Lun Li

The law of a finite graph is a probability measure induced by the orbits of the graph under its automorphism group. Every law satisfies the intrinsic mass transport principle, which is also known as unimodularity. We discuss the convergence…

Combinatorics · Mathematics 2011-03-30 Igor Artemenko

The theory of convergent graph sequences has been worked out in two extreme cases, dense graphs and bounded degree graphs. One can define convergence in terms of counting homomorphisms from fixed graphs into members of the sequence…

Combinatorics · Mathematics 2010-02-02 Christian Borgs , Jennifer Chayes , Jeff Kahn , László Lovász

The expressivity of Graph Neural Networks (GNNs) is dependent on the aggregation functions they employ. Theoretical works have pointed towards Sum aggregation GNNs subsuming every other GNNs, while certain practical works have observed a…

Machine Learning · Computer Science 2023-05-22 Eran Rosenbluth , Jan Toenshoff , Martin Grohe

In this paper, we study the consensus problem of multiple agents on a kind of famous graph, Peterson graph. It is an undirected graph with 10 vertices and 15 edges. Each agent randomly walks on this graph and communicates with each other if…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-09 Hannah Arendt , Jorgensen Jost

We prove a functional central limit theorem for subgraph counts in a dynamic version of the random connection model. To establish tightness, we develop a dynamic extension of the cumulant method.

Probability · Mathematics 2025-11-25 Rajat Subhra Hazra , Nikolai Kriukov , Michel Mandjes , Moritz Otto

The continuum limit provides a useful tool for analyzing coupled oscillator networks. Recently, Medvedev (Comm. Math. Sci., 17 (2019), no. 4, pp. 883-898) gave a mathematical foundation for such an approach when the networks are defined on…

Dynamical Systems · Mathematics 2023-06-21 Ryosuke Ihara , Kazuyuki Yagasaki

Certifying feasibility in decision-making, critical in many industries, can be framed as a constraint satisfaction problem. This paper focuses on characterising a subset of parameter values from an a priori set that satisfy constraints on a…

Systems and Control · Electrical Eng. & Systems 2025-11-14 Max Mowbray , Nilay Shah , Benoît Chachuat

This paper develops new limit theory for data that are generated by networks or more generally display cross-sectional dependence structures that are governed by observable and unobservable characteristics. Strategic network formation…

Probability · Mathematics 2019-08-08 Guido M. Kuersteiner

In this paper we study several monotonicity axioms in approval-based multi-winner voting rules. We consider monotonicity with respect to the support received by the winners and also monotonicity in the size of the committee. Monotonicity…

Computer Science and Game Theory · Computer Science 2019-02-25 Luis Sánchez-Fernández , Jesús A. Fisteus

This paper investigates the consensus problem in almost sure sense for uncertain multi-agent systems with noises and fixed topology. By combining the tools of stochastic analysis, algebraic graph theory, and matrix theory, we analyze the…

Adaptation and Self-Organizing Systems · Physics 2012-06-06 Radha F. Gupta , Poom Kumam

We consider a variant of so called power-law random graph. A sequence of expected degrees corresponds to a power-law degree distribution with finite mean and infinite variance. In previous works the asymptotic picture with number of nodes…

Probability · Mathematics 2007-12-12 Hannu Reittu , Ilkka Norros