Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
ate Abstractions of Discrete-Time Controlled Stochastic Hybrid Systems Alessandro D’Innocenzo, Alessandro Abate, and Maria D. Di Benedetto — This work proposes a procedure to c...
Alessandro D'Innocenzo, Alessandro Abate, Maria Do...
Dynamic power management in enterprise environments requires an understanding of the relationship between resource utilization and system-level power consumption. Power models bas...
There is increasing interest within the research community in the design and use of recursive probability models. There remains concern about computational complexity costs and th...
A system of stochastic differential equations is studied describing a compartmental carbon transfer model that includes uncertainties arising in the model from environmental and p...