most citedWhy Is Diagnosis Using Belief Networks Insensitive to Imprecision In Probabilities?

62 citations · 111 across the 13 of their papers we have counts for

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cs.AI20137 cited

Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (1989)

Max Henrion, Laveen Kanal, John Lemmer +1

This is the Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence, which was held in Windsor, ON, August 18-20, 1989

cs.AI20131 cited

A Framework for Comparing Uncertain Inference Systems to Probability

Ben P. Wise, Max Henrion

Several different uncertain inference systems (UISs) have been developed for representing uncertainty in rule-based expert systems. Some of these, such as Mycin's Certainty Factors…

cs.AI201313 cited

Practical Issues in Constructing a Bayes' Belief Network

Max Henrion

Bayes belief networks and influence diagrams are tools for constructing coherent probabilistic representations of uncertain knowledge. The process of constructing such a network to…

cs.AI20132 cited

A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis

Jayant Kalagnanam, Max Henrion

There has long been debate about the relative merits of decision theoretic methods and heuristic rule-based approaches for reasoning under uncertainty. We report an experimental co…

cs.AI20131 cited

How Much More Probable is "Much More Probable"? Verbal Expressions for Probability Updates

Christopher Elsaesser, Max Henrion

Bayesian inference systems should be able to explain their reasoning to users, translating from numerical to natural language. Previous empirical work has investigated the correspo…

cs.AI201310 cited

Qualitative Propagation and Scenario-based Explanation of Probabilistic Reasoning

Max Henrion, Marek J. Druzdzel

Comprehensible explanations of probabilistic reasoning are a prerequisite for wider acceptance of Bayesian methods in expert systems and decision support systems. A study of human…