Ginestra Bianconi mainly focuses on Complex network, Complex system, Statistical physics, Theoretical computer science and Degree distribution. Ginestra Bianconi interconnects Centrality, Curse of dimensionality, Quantum gravity, Entropy and Topology in the investigation of issues within Complex network. His Complex system research includes elements of Multiplex, Network theory, Structure, Node and Data science.
Ginestra Bianconi combines subjects such as Discrete mathematics, Network topology and Degree with his study of Statistical physics. His biological study spans a wide range of topics, including Cover, Node, Inference, Evolving networks and Biological network. In his work, Tetrahedron is strongly intertwined with Pure mathematics, which is a subfield of Degree distribution.
His main research concerns Statistical physics, Complex network, Topology, Phase transition and Complex system. His work deals with themes such as Function, Network dynamics, Percolation and Random graph, which intersect with Statistical physics. His Complex network research includes themes of Network topology, Information theory and Theoretical computer science.
The various areas that he examines in his Theoretical computer science study include Space and Biological network. His Topology research incorporates themes from Node, Multiplex and Interdependent networks, Robustness. His Complex system research incorporates elements of Simplicial complex, Pure mathematics, Network model, Network theory and Structure.
His primary scientific interests are in Topology, Pure mathematics, Statistical physics, Complex network and Topology. He interconnects Network topology, Multiplex, Network science and Robustness in the investigation of issues within Topology. His Pure mathematics research includes elements of Renormalization group and Order.
His Statistical physics research includes themes of Range, Phase transition and Function. His research integrates issues of Theoretical computer science, Principle of maximum entropy, Distribution, Information theory and Space in his study of Complex network. Ginestra Bianconi has researched Topology in several fields, including Clique, Node, Complex system, Betti number and Clustering coefficient.
Ginestra Bianconi mostly deals with Renormalization group, Epidemic model, Statistics, Complex network and Complex system. His study on Renormalization group also encompasses disciplines like
His Topology research is multidisciplinary, incorporating perspectives in Node, Betti number, Clustering coefficient and Network science. His Complex system study combines topics in areas such as Structure and Simplicial complex, Pure mathematics. In his study, he carries out multidisciplinary Kuramoto model and Statistical physics research.
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The structure and dynamics of multilayer networks.
S. Boccaletti;G. Bianconi;R. Criado;R. Criado;C.I. del Genio.
Physics Reports (2014)
Competition and multiscaling in evolving networks
G. Bianconi;A.-L. Barabási.
Bose-Einstein Condensation in Complex Networks
Ginestra Bianconi;Albert-László Barabási.
Physical Review Letters (2001)
Theory of rumour spreading in complex social networks
Maziar M. Nekovee;Yamir Moreno;Ginestra Bianconi;Matteo Marsili.
Physica A-statistical Mechanics and Its Applications (2007)
Statistical mechanics of multiplex networks: entropy and overlap.
Physical Review E (2013)
Entropy measures for networks: toward an information theory of complex topologies.
Kartik Anand;Ginestra Bianconi.
Physical Review E (2009)
Inhomogeneity of charge-density-wave order and quenched disorder in a high-Tc superconductor
G. Campi;A. Bianconi;N. Poccia;G. Bianconi.
Growing multiplex networks.
Vincenzo Nicosia;Ginestra Bianconi;Vito Latora;Vito Latora;Marc Barthelemy.
Physical Review Letters (2013)
Assessing the relevance of node features for network structure
Ginestra Bianconi;Paolo Pin;Matteo Marsili.
Proceedings of the National Academy of Sciences of the United States of America (2009)
The entropy of randomized network ensembles
Chaos, Solitons and Fractals
(Impact Factor: 9.922)
Profile was last updated on December 6th, 2021.
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