most citedLearning Bayesian Networks from Incomplete Data with Stochastic Search Algorithms

59 citations · 78 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI201318 cited

Proceedings of the Third Conference on Uncertainty in Artificial Intelligence (1987)

Laveen Kanal, John Lemmer, Tod Levitt

This is the Proceedings of the Third Conference on Uncertainty in Artificial Intelligence, which was held in Seattle, WA, July 10-12, 1987

cs.AI20131 cited

Proceedings of the Fourth Conference on Uncertainty in Artificial Intelligence (1988)

Laveen Kanal, John Lemmer, Tod Levitt +1

This is the Proceedings of the Fourth Conference on Uncertainty in Artificial Intelligence, which was held in Minneapolis, MN, July 10-12, 1988

cs.AI2013

Probabilistic Conflict Resolution in Hierarchical Hypothesis Spaces

Tod S. Levitt

Artificial intelligence applications such as industrial robotics, military surveillance, and hazardous environment clean-up, require situation understanding based on partial, uncer…

cs.AI2013

Bayesian Inference for Radar Imagery Based Surveillance

Tod S. Levitt

We are interested in creating an automated or semi-automated system with the capability of taking a set of radar imagery, collection parameters and a priori map and other tactical…

cs.CV2013

Model-based Influence Diagrams for Machine Vision

Tod S. Levitt, John Mark Agosta, Thomas O. Binford

We show an approach to automated control of machine vision systems based on incremental creation and evaluation of a particular family of influence diagrams that represent hypothes…

cs.AI2013

Incremental Dynamic Construction of Layered Polytree Networks

Keung-Chi Ng, Tod S. Levitt

Certain classes of problems, including perceptual data understanding, robotics, discovery, and learning, can be represented as incremental, dynamically constructed belief networks.…