Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from co...
Eugene Grois, William H. Hsu, Mikhail Voloshin, Da...
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
Abstract. As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational agents. Bayesian ...
In this paper we propose a method for on-line max auditing of dynamic statistical databases. The method extends the Bayesian approach presented in [2], [3] and [4] for static data...