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» Sequential variable sampling plan for normal distribution
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ECCV
2008
Springer
14 years 6 months ago
Window Annealing over Square Lattice Markov Random Field
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Ho Yub Jung, Kyoung Mu Lee, Sang Uk Lee
BMCBI
2007
163views more  BMCBI 2007»
13 years 8 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter
BMCBI
2006
123views more  BMCBI 2006»
13 years 8 months ago
Characterizing disease states from topological properties of transcriptional regulatory networks
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...
David Tuck, Harriet Kluger, Yuval Kluger
NN
2007
Springer
13 years 8 months ago
A neural model of decision-making by the superior colicullus in an antisaccade task
In the antisaccade paradigm subjects are instructed to perform eye movements in the opposite direction from the location of a visually appearing stimulus while they are fixating ...
Vassilis Cutsuridis, Nikolaos Smyrnis, Ioannis Evd...
UAI
2000
13 years 10 months ago
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...