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While a natural fit for modeling and understanding mobile networks, time-varying graphs remain poorly understood. Indeed, many of the usual concepts of static graphs have no obvious counterpart in time-varying ones. In this paper, we…

Networking and Internet Architecture · Computer Science 2012-08-01 John Whitbeck , Marcelo Dias de Amorim , Vania Conan , Jean-Loup Guillaume

In this article, we study branching random walks on graphs modeling division-mutation processes inspired by adaptive immunity. We apply the theory of expander graphs on mutation rules in evolutionary processes and obtain estimates for the…

Probability · Mathematics 2016-07-05 Irene Balelli , Vuk Milisic , Gilles Wainrib

We show that anomalous diffusion can result when the steps of a random walk are not statistically independent. We present an algorithm that counts all the possible paths of particles diffusing on random graphs with arbitrary degree…

Soft Condensed Matter · Physics 2007-05-23 Joseph Snider , Clare C. Yu

We study a graph-theoretic approach to the $\mathcal{H}_{\infty}$ performance of leader following consensus dynamics on directed and undirected graphs. We first provide graph-theoretic bounds on the system $\mathcal{H}_{\infty}$ norm of the…

Optimization and Control · Mathematics 2018-04-30 Mohammad Pirani , Henrik Sandberg , Karl Henrik Johansson

Dynamic connectivity is a well-studied problem, but so far the most compelling progress has been confined to the edge-update model: maintain an understanding of connectivity in an undirected graph, subject to edge insertions and deletions.…

Data Structures and Algorithms · Computer Science 2008-08-11 Timothy M. Chan , Mihai Patrascu , Liam Roditty

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

Within many real-world networks the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different…

Machine Learning · Computer Science 2020-07-07 Vincent Froese , Brijnesh Jain , Rolf Niedermeier , Malte Renken

Random walks on networks are widely used to model stochastic processes such as search strategies, transportation problems or disease propagation. A prominent example of such process is the guiding of naive T cells by the lymph node conduits…

Social and Information Networks · Computer Science 2022-10-21 Solène Song , Malek Senoussi , Paul Escande , Paul Villoutreix

Recent progress in research on Deep Graph Networks (DGNs) has led to a maturation of the domain of learning on graphs. Despite the growth of this research field, there are still important challenges that are yet unsolved. Specifically,…

Machine Learning · Computer Science 2024-04-10 Alessio Gravina , Davide Bacciu

We study the time-averaged flow in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but the graph remains finite, the large-deviation rate…

Statistical Mechanics · Physics 2020-12-02 Davide Gabrielli , D. R. Michiel Renger

The co-evolution between network structure and functional performance is a fundamental and challenging problem whose complexity emerges from the intrinsic interdependent nature of structure and function. Within this context, we investigate…

Neural and Evolutionary Computing · Computer Science 2016-05-10 Daniel R. Figueiredo , Michele Garetto

Kemeny's constant for random walks on a graph is defined as the mean hitting time from one node to another selected randomly according to the stationary distribution. It has found numerous applications and attracted considerable research…

Social and Information Networks · Computer Science 2024-09-10 Haisong Xia , Zhongzhi Zhang

The problem of a restricted random walk on graphs which keeps track of the number of immediate reversal steps is considered by using a transfer matrix formulation. A closed-form expression is obtained for the generating function of the…

Statistical Mechanics · Physics 2007-05-23 F. Y. Wu , H. Kunz

The random walk with choice is a well known variation to the random walk that first selects a subset of $d$ neighbours nodes and then decides to move to the node which maximizes the value of a certain metric; this metric captures the number…

Data Structures and Algorithms · Computer Science 2010-07-20 John Alexandris , Gregory Karagiorgos 'and' Ioannis Stavrakakis

Recently it was shown that the transitive closure of a directed graph can be updated using first-order formulas after insertions and deletions of single edges in the dynamic descriptive complexity framework by Dong, Su, and Topor, and…

Logic in Computer Science · Computer Science 2018-04-25 Samir Datta , Anish Mukherjee , Nils Vortmeier , Thomas Zeume

How to enable efficient analytics over such data has been an increasingly important research problem. Given the sheer size of such social networks, many existing studies resort to sampling techniques that draw random nodes from an online…

Social and Information Networks · Computer Science 2015-05-12 Zhuojie Zhou , Nan Zhang , Gautam Das

Temporal networks, i.e., networks in which the interactions among a set of elementary units change over time, can be modelled in terms of time-varying graphs, which are time-ordered sequences of graphs over a set of nodes. In such graphs,…

Physics and Society · Physics 2013-06-04 Vincenzo Nicosia , John Tang , Cecilia Mascolo , Mirco Musolesi , Giovanni Russo , Vito Latora

Several interesting approaches have been reported in the literature on complex networks, random walks, and hierarchy of graphs. While many of these works perform random walks on stable, fixed networks, in the present work we address the…

Social and Information Networks · Computer Science 2024-03-12 Alexandre Benatti , Luciano da F. Costa

We introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the…

Disordered Systems and Neural Networks · Physics 2015-05-13 Roni Parshani , Mark Dickison , Reuven Cohen , H. Eugene Stanley , Shlomo Havlin

This paper presents a new simulation-based approach to address the stochastic Dynamic Traffic Assignment (DTA) problem, focusing on large congested networks and dynamic settings. The proposed methodology incorporates a random walk model…

Multiagent Systems · Computer Science 2023-11-22 Kaveh Khoshkhah , Mozhgan Pourmoradnasseri , Sadok Ben Yahia , Amnir Hadachi