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Article
Open AccessInference in conditioned dynamics through causality restoration
Estimating observables from conditioned dynamics is typically computationally hard. While obtaining independent samples efficiently from unconditioned dynamics is usually feasible, most of them do not satisfy ...
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Article
Open AccessA Bayesian generative neural network framework for epidemic inference problems
The reconstruction of missing information in epidemic spreading on contact networks can be essential in the prevention and containment strategies. The identification and warning of infectious but asymptomatic ...
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Chapter and Conference Paper
Human Action Detection, Classification and Monitoring Based on Micro-Doppler Processing for Avoidance of Work Accidents
Even today, many incidents at work have fatal consequences for the workers. The availability of computational capacity and advances in compact sensor modules allows the widespread integration of real-time moni...
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Article
On the Mean Residence Time in Stochastic Lattice-Gas Models
A heuristic law widely used in fluid dynamics for steady flows states that the amount of a fluid in a control volume is the product of the fluid influx and the mean time that the particles of the fluid spend i...
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Article
Open AccessControl of Multilayer Networks
The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on is...
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Chapter and Conference Paper
Traceroute-Like Exploration of Unknown Networks: A Statistical Analysis
Map** the Internet generally consists in sampling the network from a limited set of sources by using traceroute-like probes. This methodology has been argued to introduce uncontrolled sampling biases that might...
