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Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two…

Statistical Mechanics · Physics 2013-01-17 Zhongzhi Zhang , Tong Shan , Guanrong Chen

We introduce nonlocal dynamics on directed networks through the construction of a fractional version of a nonsymmetric Laplacian for weighted directed graphs. Furthermore, we provide an analytic treatment of fractional dynamics for both…

Social and Information Networks · Computer Science 2020-08-05 Michele Benzi , Daniele Bertaccini , Fabio Durastante , Igor Simunec

We present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic…

Physics and Society · Physics 2023-09-27 Mateo Neira , Carlos Molinero , Stephen Marshall , Elsa Arcaute

Random walk neural networks (RWNNs) have emerged as a promising approach for graph representation learning, leveraging recent advances in sequence models to process random walks. However, under realistic sampling constraints, RWNNs often…

Machine Learning · Computer Science 2025-10-28 Michael Ito , Danai Koutra , Jenna Wiens

We consider a continuous-time random walk which is defined as an interpolation of a random walk on a point process on the real line. The distances between neighboring points of the point process are i.i.d. random variables in the normal…

Probability · Mathematics 2020-01-08 Alessandra Bianchi , Marco Lenci , Françoise Pène

Dynamic systems characterized by diversified evolutions are not only more flexible, but also more resilient to attacks, failures and changing conditions. This article addresses the quantification of the diversity of non-linear transient…

Physics and Society · Physics 2008-01-07 Luciano da Fontoura Costa

In modern energy networks, where operational efficiency and resilience are critical, this study introduces an in-depth analysis from a multiplex network perspective - defined as a network where multiple types of connections exist between…

Social and Information Networks · Computer Science 2025-03-20 Muhammad Kazim , Harun Pirim , Chau Le , Trung Le , Om Prakash Yadav

Many studies on animal and human movement patterns report the existence of scaling laws and power-law distributions. Whereas a number of random walk models have been proposed to explain observations, in many situations individuals actually…

Disordered Systems and Neural Networks · Physics 2015-05-13 D. Boyer , O. Miramontes , H. Larralde

Random scale-free networks are ultrasmall worlds. The average length of the shortest paths in networks of size N scales as lnlnN. Here we show that these ultrasmall worlds can be navigated in ultrashort time. Greedy routing on scale-free…

Disordered Systems and Neural Networks · Physics 2009-02-08 Marian Boguna , Dmitri Krioukov

Nowadays, mobile robots are deployed in many indoor environments, such as offices or hospitals. These environments are subject to changes in the traversability that often happen by following repeating patterns. In this paper, we investigate…

Robotics · Computer Science 2019-09-30 Lorenzo Nardi , Cyrill Stachniss

We consider random walks in which the walk originates in one set of nodes and then continues until it reaches one or more nodes in a target set. The time required for the walk to reach the target set is of interest in understanding the…

Systems and Control · Computer Science 2019-01-11 Andrew Clark , Basel Alomair , Linda Bushnell , Radha Poovendran

Random walks are fundamental tools for analyzing complex networked systems, including social networks, biological systems, and communication infrastructures. While classical random walks focus on pairwise interactions, many real-world…

Systems and Control · Electrical Eng. & Systems 2026-03-13 Anqi Dong , Anzhi Sheng , Xin Mao , Can Chen

The current article shows how concepts from the areas of random walks, Markov chains, complex networks and image analysis can be naturally combined in order to provide a unified and biologically plausible model relating saliency and visual…

Medical Physics · Physics 2007-07-04 Luciano da Fontoura Costa

In many complex systems, for the activity f(i) of the constituents or nodes i, a power-law relationship was discovered between the standard deviation sigma(i) and the average strength of the activity: sigma(i) ~ <f(i)>^alpha; universal…

Statistical Mechanics · Physics 2007-05-23 Zoltan Eisler , Janos Kertesz

Self-avoiding random walks were performed on protein residue networks. Compared with protein residue networks with randomized links, the probability of a walk being successful is lower and the length of successful walks shorter in…

Molecular Networks · Quantitative Biology 2013-06-11 Susan Khor

Robot swarms, systems of many robots that operate in a distributed fashion, have many applications in areas such as search-and-rescue, natural disaster response, and self-assembly. Several of these applications can be abstracted to the…

Multiagent Systems · Computer Science 2024-09-17 Adithya Balachandran , Noble Harasha , Nancy Lynch

Networks created and maintained by social processes, such as the human friendship network and the World Wide Web, appear to exhibit the property of navigability: namely, not only do short paths exist between any pair of nodes, but such…

Condensed Matter · Physics 2007-05-23 Aaron Clauset , Cristopher Moore

We develop an analytical approach which provides the dependence of the mean first-passage time (MFPT) for random walks on complex networks both on the target connectivity and on the source-target distance. Our approach puts forward two…

Statistical Mechanics · Physics 2015-05-27 Vincent Tejedor , Olivier Bénichou , Raphael Voituriez

We establish and generalise several bounds for various random walk quantities including the mixing time and the maximum hitting time. Unlike previous analyses, our derivations are based on rather intuitive notions of local expansion…

Probability · Mathematics 2019-03-05 Thomas Sauerwald , Luca Zanetti

Graphs are useful structures that can model several important real-world problems. Recently, learning graphs have drawn considerable attention, leading to the proposal of new methods for learning these data structures. One of these studies…

Machine Learning · Computer Science 2020-01-07 Amir Jalilifard , Vinicius Caridá , Alex Mansano , Rogers Cristo