Artículos de revistas
Inferring propagation paths for sparsely observed perturbations on complex networks
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
Massucci, Francesco Alessandro
Beltrán Debón, Raúl
Sales Pardo, Marta
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.