447 search results - page 27 / 90 » Explaining inferences in Bayesian networks |
NIPS
2008
13 years 9 months ago
2008
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
UAI
1996
13 years 9 months ago
1996
Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of th...
CVPR
1999
IEEE
14 years 9 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
HYBRID
2000
Springer
13 years 11 months ago
2000
Springer
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
INFOCOM
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract—The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. In this paper, we study the loss inferen...