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IJON
2007
93views more  IJON 2007»
13 years 7 months ago
How much can we trust neural simulation strategies?
Despite a steady improvement of computational hardware, results of numerical simulation are still tightly bound to the simulation tool and strategy used, and may substantially var...
Michelle Rudolph, Alain Destexhe
GLOBECOM
2010
IEEE
13 years 5 months ago
A Graphical Framework for Spectrum Modeling and Decision Making in Cognitive Radio Networks
There are many key problems of decision making related to spectrum occupancies in cognitive radio networks. It is known that there exist correlations of spectrum occupancies in tim...
Husheng Li, Robert C. Qiu
AMAI
2008
Springer
13 years 7 months ago
Bayesian learning of Bayesian networks with informative priors
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Nicos Angelopoulos, James Cussens
BMCBI
2010
154views more  BMCBI 2010»
13 years 7 months ago
An eScience-Bayes strategy for analyzing omics data
Background: The omics fields promise to revolutionize our understanding of biology and biomedicine. However, their potential is compromised by the challenge to analyze the huge da...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg
AI
2007
Springer
14 years 1 months ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel