Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more e...
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
Teaser Figure: Left: Brain, visualized using silhouettes, the lesion's spatial depth is displayed using a ring. Center: Combined rendering of brain tissue, skull and fiber tr...
Christian Rieder, Felix Ritter, Matthias Raspe, He...
There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric model...
Nicolas Delannay, Fabrice Rossi, Brieuc Conan-Guez...
Effective analysis of genome sequences and associated functional data requires access to many different kinds of biological information. For example, when analysing gene expressio...
Mike Cornell, Norman W. Paton, Shengli Wu, Carole ...
Probability distributions are central tools for probabilistic modeling in data mining, and they lack in functional data analysis (FDA). In this paper we propose a probability dist...