Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31143 
Year of Publication: 
2003
Series/Report no.: 
Discussion Paper No. 348
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
Typical problems in the analysis of data sets like time-series or images crucially rely on the extraction of primitive features based on segmentation. Variational approaches are a popular and convenient framework in which such problems can be studied. We focus on Potts models as simple nontrivial instances. The discussion proceeds along two data sets from brain mapping and functional genomics.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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