One of the major weaknesses of current research on the Semantic Web (SW) is the lack of proper means to represent and reason with uncertainty. A number of recent efforts from the ...
Paulo Cesar G. da Costa, Marcelo Ladeira, Rommel N...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Bayesian networks (BNs) provide a means for representing, displaying, and making available in a usable form the knowledge of experts in a given Weld. In this paper, we look at the...
Traditional hop-by-hop dynamic routing makes inefficient use of network resources as it forwards packets along already congested shortest paths while uncongested longer paths may b...
Minsoo Lee, Xiaohui Ye, Dan Marconett, Samuel John...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...