We introduce a computationally efficient method to estimate the validity of the BP method as a function of graph topology, the connectivity strength, frustration and network size....
: Recently lots of studies aim at modeling and inferring gene networks. Modeling tools propose graphical models having almost nothing about time description of events and regards t...
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the...
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...