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networksNetworks, Graph Theory The patientzero problem with noisy observationThe patientzero problem consists in finding the initial source of an epidemic outbreak given observations at a later time. In this seminar, I will describe a Bayesian method which is able to infer details on the past history of an epidemics based solely on the topology of the contact network and a single snapshot of partial and noisy observations. The method is built on a Bethe approximation for the posterior distribution, and is inherently exact on tree graphs. Moreover, it can be coupled to a set of equations, based on the variational expression of the Bethe free energy, to find the patientzero along with maximumlikelihood epidemic parameters. Date:
Thu, 30/10/2014  14:30
Speaker:
Alessandro Ingrosso
Place:
HuGeF, Via Nizza 52
Bayesian inference of epidemics on networkI study inference problems for irreversible stochastic epidemic models on network via Belief Propagation algorithm. Previous works derive equations which allow to compute posterior distributions of the time evolution of the state of each node given some observation. It has already been shown that this method outperforms previous ones in the particular case of finding "patient zero" of a SIR epidemic given an observation at a later unknown time. I study performances of this method on the inference of the time evolution of a SIR epidemic subsequent a given observation. Date:
Thu, 16/10/2014  14:30
Speaker:
Jacopo Bindi
A cavitymethod based approach to the Steiner tree problem on graphsThe minimum weight Steiner tree problem (MST) is an important combinatorial optimization problem over networks that has applications in a wide range of ﬁelds. I will mainly focus my attention on two variants of the problem: Date:
Thu, 23/10/2014  14:30
Speaker:
Anna Paola Muntoni
Perturbation Biology: Inferring Signaling Networks in Cellular Systems
Perturbation Biology: Inferring Signaling Networks in Cellular Systems. PLoS Computational Biology. 2013;9(12):e1003290.
Optimizing spread dynamics on graphs by message passing
Optimizing spread dynamics on graphs by message passing. Journal of Statistical Mechanics: Theory and Experiment. 2013;2013(09):P09011.
Large deviations of cascade processes on graphs
Large deviations of cascade processes on graphs. Phys. Rev. E. 2013;87:062115.
Spatial disorder in the Voter ModelWhen we try to study the organization and the properties of ecological systems, nonequilibrium statistical physics is a natural candidate to develop a unified framework for understanding the emergent properties of these kind of systems. Simple interacting particle systems, such as the Voter Model (VM), have found a surprisingly good agreement with empirical data and proved to be a useful nullmodel that can be treated analytically. Despite the recent progress in this field, still a major issue in ecology and conservation ecology is to understand the effects of habitat fragmentation and heterogeneities on the biodiversity of an ecosystem. Motivated by this open problem, we study the effects of quenched spatial disorder on the longtime behavior of the VM and its nonlinear generalizations. Date:
Wed, 12/12/2012  15:00
Speaker:
Claudio Borile
Collaboration in social networks
Collaboration in social networks. Proceedings of the National Academy of Sciences. 2012;109:4395400.
Statistical physics approach to graphical games: local and global interactions
Statistical physics approach to graphical games: local and global interactions. Eur. Phys. J. B. 2011;81(3).
Optimal equilibria of the best shot game
Optimal equilibria of the best shot game. Journal of Public Economic Theory. 2011;13(6).
