This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The dat...
This paper describes the use of dynamic Bayesian networks for the task of articulatory feature recognition. We show that by modeling the dependencies between a set of 6 multi-leve...
The vision-based scene understanding technique that infers scene-interpreting contexts from real-world vision data has to not only deal with various uncertain environments but also...
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...