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» Sources of Variability in MEG
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ICA
2007
Springer
15 years 1 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
83
Voted
ICIS
2003
14 years 11 months ago
Defining Open Source Software Project Success
Information systems success is one of the most widely used dependent variables in information systems research. In this paper, we identify a range of measures that can be used to ...
Kevin Crowston, Hala Annabi, James Howison
BMCBI
2006
154views more  BMCBI 2006»
14 years 9 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...
DAC
2005
ACM
14 years 11 months ago
Mapping statistical process variations toward circuit performance variability: an analytical modeling approach
A physical yet compact gate delay model is developed integrating short-channel effects and the Alpha-power law based timing model. This analytical approach accurately predicts bot...
Yu Cao, Lawrence T. Clark
BMCBI
2010
123views more  BMCBI 2010»
14 years 9 months ago
Computationally efficient flux variability analysis
Background: Flux variability analysis is often used to determine robustness of metabolic models in various simulation conditions. However, its use has been somehow limited by the ...
Steinn Gudmundsson, Ines Thiele