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» A Functional Model for Data Analysis
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ICCS
2003
Springer
15 years 4 months ago
Parallelisation of Sparse Grids for Large Scale Data Analysis
Sparse Grids are the basis for efficient high dimensional approximation and have recently been applied successfully to predictive modelling. They are spanned by a collection of si...
Jochen Garcke, Markus Hegland, Ole Møller N...
IJON
2008
114views more  IJON 2008»
14 years 11 months ago
A robust model for spatiotemporal dependencies
Real-world data sets such as recordings from functional magnetic resonance imaging often possess both spatial and temporal structure. Here, we propose an algorithm including such ...
Fabian J. Theis, Peter Gruber, Ingo R. Keck, Elmar...
TMI
2008
138views more  TMI 2008»
14 years 10 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
JCISE
2002
117views more  JCISE 2002»
14 years 10 months ago
Memory Analysis of Solid Model Representations for Heterogeneous Objects
Methods to represent and exchange parts consisting of Functionally Graded Material (FGM) for Solid Freeform Fabrication (SFF) with Local Composition Control (LCC) are evaluated ba...
Todd R. Jackson, Wonjoon Cho, Nicholas M. Patrikal...
BMCBI
2005
140views more  BMCBI 2005»
14 years 11 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...