315 citations
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Showing 2013 · cs.AIShow all
3 papers · 2 filters
cs.AI2013
Investigation of Variances in Belief Networks
Richard E. Neapolitan, James Kenevan
The belief network is a well-known graphical structure for representing independences in a joint probability distribution. The methods, which perform probabilistic inference in bel…
cs.AI2013
An Implementation of a Method for Computing the Uncertainty in Inferred Probabilities in Belief Networks
Peter Che, Richard E. Neapolitan, James Kenevan +1
In recent years the belief network has been used increasingly to model systems in Al that must perform uncertain inference. The development of efficient algorithms for probabilisti…
cs.AI2013★ 5 cited
The Cognitive Processing of Causal Knowledge
Scott B. Morris, Doug Cork, Richard E. Neapolitan
There is a brief description of the probabilistic causal graph model for representing, reasoning with, and learning causal structure using Bayesian networks. It is then argued that…