We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
In multiowner wireless networks, access points (APs) are owned and operated by different administrations, leading to significant authentication delays during handoff between APs. W...
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...