One of the most important problems for an intelligent tutoring system is deciding how to respond when a student asks for help. Responding cooperatively requires an understanding o...
Abstract. It is difficult to understand a scene from visual information in uncertain real world. Since Bayesian network (BN) is known as good in this uncertainty, it has received s...
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
In many reliability studies based on data, reliability engineers face incompleteness and incoherency problems in the data. Probabilistic tools badly handle these kinds of problems...