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NIPS
2001
15 years 8 months ago
MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation
Bayesian belief propagation in graphical models has been recently shown to have very close ties to inference methods based in statistical physics. After Yedidia et al. demonstrate...
Anand Rangarajan, Alan L. Yuille
METMBS
2003
255views Mathematics» more  METMBS 2003»
15 years 8 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
UAI
2003
15 years 8 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
IJCAI
1989
15 years 7 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter
GISCIENCE
2010
Springer
244views GIS» more  GISCIENCE 2010»
15 years 7 months ago
Detecting Road Intersections from GPS Traces
As an alternative to expensive road surveys, we are working toward a method to infer the road network from GPS data logged from regular vehicles. One of the most important componen...
Alireza Fathi, John Krumm