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dc.contributor.author
Massucci, Francesco Alessandro
dc.contributor.author
Wheeler, Jonathan
dc.contributor.author
Beltrán Debón, Raúl
dc.contributor.author
Joven, Jorge
dc.contributor.author
Sales Pardo, Marta
dc.contributor.author
Guimerà, Roger
dc.date.available
2018-09-12T22:17:08Z
dc.date.issued
2016-10
dc.identifier.citation
Massucci, Francesco Alessandro; Wheeler, Jonathan; Beltrán Debón, Raúl; Joven, Jorge; Sales Pardo, Marta; et al.; Inferring propagation paths for sparsely observed perturbations on complex networks; American Association for the Advancement of Science; Science Advances; 2; 10; 10-2016; 1-9; e1501638
dc.identifier.issn
2375-2548
dc.identifier.uri
http://hdl.handle.net/11336/59470
dc.description.abstract
In a complex system, perturbations propagate by following paths on the network of interactions among the system's units. In contrast to what happens with the spreading of epidemics, observations of general perturbations are often very sparse in time (there is a single observation of the perturbed system) and in "space" (only a few perturbed and unperturbed units are observed). A major challenge in many areas, from biology to the social sciences, is to infer the propagation paths from observations of the effects of perturbation under these sparsity conditions. We address this problem and show that it is possible to go beyond the usual approach of using the shortest paths connecting the known perturbed nodes. Specifically, we show that a simple and general probabilistic model, which we solved using belief propagation, provides fast and accurate estimates of the probabilities of nodes being perturbed.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Association for the Advancement of Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.subject
Complex Networks
dc.subject
Inference
dc.subject
Belief Propagation
dc.subject
Perturbed Systems
dc.subject.classification
Astronomía
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Ciencias Físicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Inferring propagation paths for sparsely observed perturbations on complex networks
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-09-04T16:35:42Z
dc.journal.volume
2
dc.journal.number
10
dc.journal.pagination
1-9; e1501638
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Washington DC
dc.description.fil
Fil: Massucci, Francesco Alessandro. Universitat Rovira I Virgili; España
dc.description.fil
Fil: Wheeler, Jonathan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Universitat Rovira I Virgili; España
dc.description.fil
Fil: Beltrán Debón, Raúl. Universitat Rovira I Virgili; España
dc.description.fil
Fil: Joven, Jorge. Universitat Rovira I Virgili; España
dc.description.fil
Fil: Sales Pardo, Marta. Universitat Rovira I Virgili; España
dc.description.fil
Fil: Guimerà, Roger. Institució Catalana de Recerca i Estudis Avancats; España. Universitat Rovira I Virgili; España
dc.journal.title
Science Advances
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://advances.sciencemag.org/content/2/10/e1501638.full
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1126/sciadv.1501638
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