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» Importance Sampling for Continuous Time Bayesian Networks
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BMCBI
2008
201views more  BMCBI 2008»
14 years 9 months ago
A copula method for modeling directional dependence of genes
Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can b...
Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap...
93
Voted
NIPS
2004
14 years 11 months ago
Dynamic Bayesian Networks for Brain-Computer Interfaces
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
Pradeep Shenoy, Rajesh P. N. Rao
WICON
2008
14 years 11 months ago
SAMPL: a simple aggregation and message passing layer for sensor networks
In recent years, wireless sensor networking has shown great promise in applications ranging from industrial control, environmental monitoring and inventory tracking. Given the res...
Anthony Rowe, Karthik Lakshmanan, Ragunathan Rajku...
SUTC
2010
IEEE
15 years 1 months ago
A Log-Ratio Information Measure for Stochastic Sensor Management
—In distributed sensor networks, computational and energy resources are in general limited. Therefore, an intelligent selection of sensors for measurements is of great importance...
Daniel Lyons, Benjamin Noack, Uwe D. Hanebeck
83
Voted
NIPS
2008
14 years 11 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould