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We propose a method to efficiently estimate the Laplacian eigenvalues of an arbitrary, unknown network of interacting dynamical agents. The inputs to our estimation algorithm are measurements about the evolution of a collection of agents…

Spectral Theory · Mathematics 2019-12-09 Mikhail Hayhoe , Francisco Barreras , Victor M. Preciado

We consider the problem of optimizing the interconnection graphs of complex networks to promote synchronization. When traditional optimization methods are inapplicable, due to uncertain or unknown node dynamics, we propose a data-driven…

Systems and Control · Electrical Eng. & Systems 2023-09-29 Marco Coraggio , Mario di Bernardo

The dynamics of distributed sources is described by nonlinear partial differential equations. Lagrangian analytical solutions of these (and associated) equations are obtained and discussed in the context of Lagrangian modeling - from the…

Pattern Formation and Solitons · Physics 2007-05-23 E. A. Novikov

Conservation laws and balance equations for physical network systems typically can be described with the aid of the incidence matrix of a directed graph, and an associated symmetric Laplacian matrix. Some basic examples are discussed, and…

Optimization and Control · Mathematics 2015-10-19 A. J. van der Schaft

We introduce a strategy of navigation in undirected networks, including regular, random, and complex networks, that is inspired by L\'evy random walks, generalizing previous navigation rules. We obtained exact expressions for the stationary…

Statistical Mechanics · Physics 2012-11-22 A. P. Riascos , José L. Mateos

This note introduces a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of undirected graphs with self-loops. We extend on the known results for the spectrum of undirected graphs without self-loops or…

Optimization and Control · Mathematics 2015-06-09 Behcet Acikmese

We study the problem of distributed hypothesis testing with a network of agents where some agents repeatedly gain access to information about the correct hypothesis. The group objective is to globally agree on a joint hypothesis that best…

Optimization and Control · Mathematics 2015-08-24 Angelia Nedić , Alex Olshevsky , César A. Uribe

Can evolving networks be inferred and modeled without directly observing their nodes and edges? In many applications, the edges of a dynamic network might not be observed, but one can observe the dynamics of stochastic cascading processes…

Machine Learning · Computer Science 2019-02-26 Elahe Ghalebi , Baharan Mirzasoleiman , Radu Grosu , Jure Leskovec

Localized perturbations in a real-world network have the potential to trigger cascade failures at the whole system level, hindering its operations and functions. Standard approaches analytically tackling this problem are mostly based either…

Physics and Society · Physics 2022-04-19 Angelo Valente , Manlio De Domenico , Oriol Artime

The configuration model was originally defined for undirected networks and has recently been extended to directed networks. Many empirical networks are however neither undirected nor completely directed, but instead usually partially…

Probability · Mathematics 2015-09-30 Kristoffer Spricer , Tom Britton

We consider linear dynamical systems with a structure of a multigraph. The vertices are associated to linear spaces and the edges correspond to linear maps between those spaces. We analyse the asymptotic growth of trajectories (associated…

Dynamical Systems · Mathematics 2016-07-05 Antonio Cicone , Nicola Guglielmi , Vladimir Protasov

We consider random walks on dynamical networks where edges appear and disappear during finite time intervals. The process is grounded on three independent stochastic processes determining the walker's waiting-time, the up-time and down-time…

Physics and Society · Physics 2018-11-28 Julien Petit , Martin Gueuning , Timoteo Carletti , Ben Lauwens , Renaud Lambiotte

This paper introduces a novel direct approach to system identification of dynamic networks with missing data based on maximum likelihood estimation. Dynamic networks generally present a singular probability density function, which poses a…

Systems and Control · Electrical Eng. & Systems 2024-07-31 João Victor Galvão da Mata , Anders Hansson , Martin S. Andersen

Pedestrian trajectory prediction is a challenging task because of the complexity of real-world human social behaviors and uncertainty of the future motion. For the first issue, existing methods adopt fully connected topology for modeling…

Computer Vision and Pattern Recognition · Computer Science 2019-07-25 Lidan Zhang , Qi She , Ping Guo

In this paper, we investigate the controllability of a linear time-invariant network following a Laplacian dynamics defined on a threshold graph. In this direction, an algorithm for deriving the modal matrix associated with the Laplacian…

Optimization and Control · Mathematics 2019-04-23 Shima Sadat Mousavi , Mohammad Haeri , Mehran Mesbahi

Large unweighted directed graphs are commonly used to capture relations between entities. A fundamental problem in the analysis of such networks is to properly define the similarity or dissimilarity between any two vertices. Despite the…

Machine Learning · Statistics 2015-11-03 Tatsunori B. Hashimoto , Yi Sun , Tommi S. Jaakkola

Complex real-world phenomena are often modeled as dynamical systems on networks. In many cases of interest, the spectrum of the underlying graph Laplacian sets the system stability and ultimately shapes the matter or information flow. This…

Statistical Mechanics · Physics 2020-05-13 Sara Nicoletti , Timoteo Carletti , Duccio Fanelli , Giorgio Battistelli , Luigi Chisci

Motion planning is a fundamental problem of robotics with applications in many areas of computer science and beyond. Its restriction to graphs has been investigated in the literature for it allows to concentrate on the combinatorial problem…

Discrete Mathematics · Computer Science 2009-04-14 Zhilin Wu , Stephane Grumbach

A survey is made of several aspects of the dynamics of networks, with special emphasis on unsupervised learning processes, non-Gaussian data analysis and pattern recognition in networks with complex nodes.

Disordered Systems and Neural Networks · Physics 2009-09-25 R. Vilela Mendes

Constructing and studying distributed control systems requires the analysis of the Laplacian spectra and the forest structure of directed graphs. In this paper, we present some basic results of this analysis partially obtained by the…

Multiagent Systems · Computer Science 2009-03-20 Pavel Chebotarev , Rafig Agaev
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