This site uses cookies to deliver our services and to ensure you get the best experience. By continuing to use this site, you consent to our use of cookies and acknowledge that you have read and understand our Privacy Policy, Cookie Policy, and Terms
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We developed a general methodology for modelling reliability of complex systems based o...
Bayesian network is a widely used tool for data analysis, modeling and decision support in various domains. There is a growing need for techniques and tools which can automatically...
This work casts the traffic analysis of anonymity systems, and in particular mix networks, in the context of Bayesian inference. A generative probabilistic model of mix network ar...
Previous work on sensitivity analysis in Bayesian networks has focused on single parameters, where the goal is to understand the sensitivity of queries to single parameter changes...