29 citations · 52 across the 16 of their papers we have counts for
3 papers · 1 filter
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning
Adrien Lagrange, Mathieu Fauvel, Stéphane May +1
Within a supervised classification framework, labeled data are used to learn classifier parameters. Prior to that, it is generally required to perform dimensionality reduction via…
Bayesian nonparametric Principal Component Analysis
Clément Elvira, Pierre Chainais, Nicolas Dobigeon
Principal component analysis (PCA) is very popular to perform dimension reduction. The selection of the number of significant components is essential but often based on some practi…
Unmixing dynamic PET images with variable specific binding kinetics
Yanna Cruz Cavalcanti, Thomas Oberlin, Nicolas Dobigeon +3
To analyze dynamic positron emission tomography (PET) images, various generic multivariate data analysis techniques have been considered in the literature, such as principal compon…