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WSC
1998
14 years 11 months ago
Bayesian Model Selection when the Number of Components is Unknown
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
Russell C. H. Cheng
NIPS
2008
14 years 11 months ago
Hebbian Learning of Bayes Optimal Decisions
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...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
CMSB
2009
Springer
15 years 4 months ago
A Bayesian Approach to Model Checking Biological Systems
Recently, there has been considerable interest in the use of Model Checking for Systems Biology. Unfortunately, the state space of stochastic biological models is often too large f...
Sumit Kumar Jha, Edmund M. Clarke, Christopher Jam...
ICIP
2007
IEEE
15 years 11 months ago
The Hough Transform's Implicit Bayesian Foundation
This paper shows that the basic Hough transform is implicitly a Bayesian process--that it computes an unnormalized posterior distribution over the parameters of a single shape giv...
Neil Toronto, Bryan S. Morse, Dan Ventura, Kevin D...
ICPR
2004
IEEE
15 years 11 months ago
Skin Detection: A Bayesian Network Approach
The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach...
Ira Cohen, Nicu Sebe, Theo Gevers, Thomas S. Huang