This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...