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We study the robustness properties of multiplex networks consisting of multiple layers of distinct types of links, focusing on the role of correlations between degrees of a node in different layers. We use generating function formalism to…

Physics and Society · Physics 2014-05-02 Byungjoon Min , Su Do Yi , Kyu-Min Lee , K. -I. Goh

Vertex classification -- the problem of identifying the class labels of nodes in a graph -- has applicability in a wide variety of domains. Examples include classifying subject areas of papers in citation networks or roles of machines in a…

Social and Information Networks · Computer Science 2023-08-11 Benjamin A. Miller , Kevin Chan , Tina Eliassi-Rad

Dynamics in biological networks are in general robust against several perturbations. We investigate a coupled map network as a model motivated by gene regulatory networks and design systems which are robust against phenotypic perturbations…

Molecular Networks · Quantitative Biology 2015-03-20 Nen Saito , Macoto Kikuchi

We study asymptotic dynamical patterns that emerge among a set of nodes interacting in a dynamically evolving signed random network, where positive links carry out standard consensus and negative links induce relative-state flipping. A…

Social and Information Networks · Computer Science 2014-12-08 Guodong Shi , Alexandre Proutiere , Mikael Johansson , John. S. Baras , Karl H. Johansson

We propose a unified framework for robustly and adaptively stabilizing large-scale networked uncertain Markovian jump linear systems (MJLS) under external disturbances and mode switches that can change the network's topology. Adaptation is…

Systems and Control · Electrical Eng. & Systems 2024-08-29 SooJean Han , Minwoo M. Kim , Ieun Choo

Simple nonlinear dynamical systems with multiple stable stationary states are often taken as models for switchlike biological systems. This paper considers the interaction of multiple such simple multistable systems when they are embedded…

Quantitative Methods · Quantitative Biology 2008-04-10 Dennis Cates Wylie

A central issue in complex networks is tolerance to random failures and intentional attacks. Current literature emphasizes the dichotomy between networks with a power-law node connectivity distribution, which are robust to random failures…

Statistical Mechanics · Physics 2009-11-10 Andre X. C. N. Valente , Abhijit Sarkar , Howard A. Stone

We consider the problem of embedding a dynamic network, to obtain time-evolving vector representations of each node, which can then be used to describe changes in behaviour of individual nodes, communities, or the entire graph. Given this…

Machine Learning · Statistics 2022-01-21 Ian Gallagher , Andrew Jones , Patrick Rubin-Delanchy

In quasi-two-dimensional experiments with photoelastic particles confined to an annular region, an intruder constrained to move in a circular path halfway between the annular walls experiences stick-slip dynamics. We discuss the response of…

Soft Condensed Matter · Physics 2025-07-30 R. Basak , R. Kozlowski , L. A. Pugnaloni , M. Kramar , E. S. Socolar , C. M. Carlevaro , L. Kondic

We introduce a simple model of static networks, where nodes are located on a ring structure, and two accompanying dynamic rules of repeated averaging on periodic node states. We assume nodes can interact with neighbors, and will add…

Physics and Society · Physics 2012-03-16 Suhan Ree

In this work, we study the dynamical robustness in a system consisting of both active and inactive oscillators. We analytically show that the dynamical robustness of such system is determined by the cross link density between active and…

Adaptation and Self-Organizing Systems · Physics 2017-03-01 Wenwen Huang , Xiyun Zhang , Xin Hu , Zonghua Liu , Shuguang Guan

A Boolean network is a finite dynamical system, whose variables take values from a binary set. The value update rule for each variable is a Boolean function, depending on a selected subset of variables. Boolean networks have been widely…

Dynamical Systems · Mathematics 2017-08-10 Zuguang Gao , Xudong Chen , Tamer Başar

Species interaction networks are a powerful tool for describing ecological communities; they typically contain nodes representing species, and edges representing interactions between those species. For the purposes of drawing abstract…

Machine Learning · Computer Science 2025-02-25 Sanaz Hasanzadeh Fard , Emily Dolson

We study asymptotic dynamical patterns that emerge among a set of nodes that interact in a dynamically evolving signed random network. Node interactions take place at random on a sequence of deterministic signed graphs. Each node receives…

Social and Information Networks · Computer Science 2013-09-24 Guodong Shi , Alexandre Proutiere , Mikael Johansson , John. S. Baras , Karl H. Johansson

The emergence and evolution of real-world systems have been extensively studied in the last few years. However, equally important phenomena are related to the dynamics of systems' collapse, which has been less explored, especially when they…

Physics and Society · Physics 2019-09-27 Jie Li , Chengyi Xia , Gaoxi Xiao , Yamir Moreno

Neural networks are known to be highly sensitive to adversarial examples. These may arise due to different factors, such as random initialization, or spurious correlations in the learning problem. To better understand these factors, we…

Machine Learning · Statistics 2022-07-05 Elvis Dohmatob , Alberto Bietti

This article examines the impact of Hamiltonian dynamics on the interaction graph of Boolean networks. Three types of dynamics are considered: maximum height, Hamiltonian cycle, and an intermediate dynamic between these two. The study…

Discrete Mathematics · Computer Science 2026-05-14 Arturo Zapata-Cortés , Julio Aracena

It has recently been suggested \cite{Radicchi2013} that in a two-level multiplex network, a gradual change in the value of the "interlayer" strength $p$ can provoke an abrupt structural transition. The critical point $p^*$ at which this…

Statistical Mechanics · Physics 2015-06-23 Nikolaos Bastas , Filippos Lazaridis , Panos Argyrakis , Michael Maragakis

A growing family of random graphs is called robust if it retains a giant component after percolation with arbitrary positive retention probability. We study robustness for graphs, in which new vertices are given a spatial position on the…

Probability · Mathematics 2015-04-08 Emmanuel Jacob , Peter Morters

Nonlinear networked systems are of interest in several areas of research, such as multi-agent systems and social networks. In this paper, we examine the controllability of several classes of nonlinear networked dynamics on which the…

Optimization and Control · Mathematics 2017-09-21 Mathias Hudoba de Badyn , Siavash Alemzadeh , Mehran Mesbahi