activity
20112013
most citedElicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information

176 citations · 538 across the 16 of their papers we have counts for

collaborators

16 papers

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…

cs.AI2013

Intercausal Reasoning with Uninstantiated Ancestor Nodes

Marek J. Druzdzel, Max Henrion

Intercausal reasoning is a common inference pattern involving probabilistic dependence of causes of an observed common effect. The sign of this dependence is captured by a qualitat…

cs.AI2013

Causality in Bayesian Belief Networks

Marek J. Druzdzel, Herbert A. Simon

We address the problem of causal interpretation of the graphical structure of Bayesian belief networks (BBNs). We review the concept of causality explicated in the domain of struct…

cs.AI2013

Some Properties of Joint Probability Distributions

Marek J. Druzdzel

Several Artificial Intelligence schemes for reasoning under uncertainty explore either explicitly or implicitly asymmetries among probabilities of various states of their uncertain…

cs.AI2013176 cited

Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information

Marek J. Druzdzel, Linda C. van der Gaag

Although the usefulness of belief networks for reasoning under uncertainty is widely accepted, obtaining numerical probabilities that they require is still perceived a major obstac…

cs.AI201339 cited

Computational Advantages of Relevance Reasoning in Bayesian Belief Networks

Yan Lin, Marek J. Druzdzel

This paper introduces a computational framework for reasoning in Bayesian belief networks that derives significant advantages from focused inference and relevance reasoning. This f…