S
Stefano Boccaletti
Researcher at Moscow Institute of Physics and Technology
Publications - 361
Citations - 29686
Stefano Boccaletti is an academic researcher from Moscow Institute of Physics and Technology. The author has contributed to research in topics: Complex network & Synchronization (computer science). The author has an hindex of 60, co-authored 348 publications receiving 25776 citations. Previous affiliations of Stefano Boccaletti include King Juan Carlos University & Istituto Nazionale di Fisica Nucleare.
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Journal ArticleDOI
Combining complex networks and data mining: why and how
Massimiliano Zanin,David Papo,Pedro Sousa,Ernestina Menasalvas,Andrea Nicchi,Elaine Kubik,Stefano Boccaletti +6 more
TL;DR: In this paper, an overview of both fields is provided, some fundamental concepts of which are illustrated, and a variety of contexts in which complex network theory and data mining have been used in a synergistic manner are presented.
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Inter-layer synchronization in multiplex networks of identical layers
Ricardo Sevilla-Escoboza,Irene Sendiña-Nadal,Inmaculada Leyva,Inmaculada Leyva,Ricardo Gutiérrez,Javier M. Buldú,Javier M. Buldú,Stefano Boccaletti +7 more
TL;DR: This work analytically derive the necessary conditions for the existence and stability of inter-layer synchronization, and verifies numerically the analytical predictions in several cases where such a state emerges.
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Optimizing Functional Network Representation of Multivariate Time Series
Massimiliano Zanin,Massimiliano Zanin,Pedro Sousa,David Papo,Ricardo Bajo,Juan García-Prieto,Francisco del Pozo,Ernestina Menasalvas,Stefano Boccaletti +8 more
TL;DR: By combining complex network theory and data mining techniques, this work proposes a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes.
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Dynamical network model of infective mobile agents.
TL;DR: This work investigates the main properties of the dynamical network introduced to model the spread of an infectious disease in a population of mobile individuals, and shows that peculiar features arise when individuals are allowed to perform long-distance jumps.
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Emerging Meso- and Macroscales from Synchronization of Adaptive Networks
Ricardo Gutiérrez,Andreas Amann,Salvatore Assenza,Jesús Gómez-Gardeñes,Vito Latora,Stefano Boccaletti +5 more
TL;DR: It is shown that a competitive mechanism leads to the emergence of a rich modular structure underlying cluster synchronization, and to a scale-free distribution for the connection strengths of the units.