Simulation built on assumption and approximation has been traditionally utilized to make predictions prior to construction. Although there are many benefits of simulation such as ...
Tae Hwan Chung, Yasser Mohamed, Simaan M. AbouRizk
This paper reports our investigation on the problem of belief update in Bayesian networks (BN) using uncertain evidence. We focus on two types of uncertain evidences, virtual evid...
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
There is a diversity of functional genomics data, such as gene expression data from microarray experiments, phenotypic data from gene deletion experiments, protein-protein interac...
Taking into account input-model, input-parameter, and stochastic uncertainties inherent in many simulations, our Bayesian approach to input modeling yields valid point and confide...