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» Explaining inferences in Bayesian networks
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AAAI
2006
13 years 9 months ago
Performing Incremental Bayesian Inference by Dynamic Model Counting
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...
Wei Li 0002, Peter van Beek, Pascal Poupart
WWW
2005
ACM
14 years 8 months ago
Association search in semantic web: search + inference
Association search is to search for certain instances in semantic web and then make inferences from and about the instances we have found. In this paper, we propose the problem of...
Bangyong Liang, Jie Tang, Juan-Zi Li
BMCBI
2007
143views more  BMCBI 2007»
13 years 7 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
ECAI
2010
Springer
13 years 7 months ago
The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
Johan Kwisthout, Hans L. Bodlaender, Linda C. van ...
AUSAI
2005
Springer
14 years 1 months ago
Conditioning Graphs: Practical Structures for Inference in Bayesian Networks
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
Kevin Grant, Michael C. Horsch