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IJPRAI
2000
83views more  IJPRAI 2000»
14 years 11 months ago
Practical Issues in Modeling Large Diagnostic Systems with Multiply Sectioned Bayesian Networks
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
114
Voted
ACIVS
2006
Springer
15 years 3 months ago
Interactive Learning of Scene Context Extractor Using Combination of Bayesian Network and Logic Network
The vision-based scene understanding technique that infers scene-interpreting contexts from real-world vision data has to not only deal with various uncertain environments but also...
Keum-Sung Hwang, Sung-Bae Cho
IROS
2007
IEEE
125views Robotics» more  IROS 2007»
15 years 6 months ago
Probabilistic inference for structured planning in robotics
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
Marc Toussaint, Christian Goerick
VLSID
2006
IEEE
129views VLSI» more  VLSID 2006»
16 years 1 days ago
A Stimulus-Free Probabilistic Model for Single-Event-Upset Sensitivity
With device size shrinking and fast rising frequency ranges, effect of cosmic radiations and alpha particles known as Single-Event-Upset (SEU), Single-Eventtransients (SET), is a ...
Mohammad Gh. Mohammad, Laila Terkawi, Muna Albasma...
97
Voted
IJCNN
2008
IEEE
15 years 6 months ago
A comparison of bayesian and conditional density models in probabilistic ozone forecasting
— Probabilistic models were developed to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models were compared at two stations ...
Song Cai, William W. Hsieh, Alex J. Cannon