We consider probabilistic inference in general hybrid networks, which include continuous and discrete variables in an arbitrary topology. We reexamine the question of variable dis...
Recursive graphical models usually underlie the statistical modelling concerning probabilistic expert systems based on Bayesian networks. This paper de nes a version of these mode...
In previous work [BGHK92, BGHK93], we have studied the random-worlds approach--a particular (and quite powerful) method for generating degrees of belief (i.e., subjective probabil...
Fahiem Bacchus, Adam J. Grove, Joseph Y. Halpern, ...
We compare the diagnostic accuracy of three diagnostic inference models: the simple Bayes model, the multimembership Bayes model, which is isomorphic to the parallel combination f...
In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...