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» Explaining inferences in Bayesian networks
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PERCOM
2010
ACM
13 years 5 months ago
Faster Bayesian context inference by using dynamic value ranges
—This paper shows how to reduce evaluation time for context inference. Probabilistic Context Inference has proven to be a good representation of the physical reality with uncerta...
Korbinian Frank, Patrick Robertson, Sergio Fortes ...
IJAR
2006
80views more  IJAR 2006»
13 years 7 months ago
Operations for inference in continuous Bayesian networks with linear deterministic variables
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
Barry R. Cobb, Prakash P. Shenoy
IJCNN
2008
IEEE
14 years 1 months ago
Out-of-body experiences: False climbs in a supine position?
— Out-of-body experiences (OBEs) are illusions, where people experience themselves as being located outside their physical body and often flying or floating at an elevated loca...
Lars Schwabe, Olaf Blanke
BMCBI
2007
164views more  BMCBI 2007»
13 years 7 months ago
Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...
NIPS
1998
13 years 8 months ago
Inference in Multilayer Networks via Large Deviation Bounds
We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
Michael J. Kearns, Lawrence K. Saul