Search Results for author: Gastone Castellani

Found 2 papers, 1 papers with code

WISDoM: characterizing neurological timeseries with the Wishart distribution

no code implementations28 Jan 2020 Carlo Mengucci, Daniel Remondini, Gastone Castellani, Enrico Giampieri

WISDoM (Wishart Distributed Matrices) is a new framework for the quantification of deviation of symmetric positive-definite matrices associated to experimental samples, like covariance or correlation matrices, from expected ones governed by the Wishart distribution WISDoM can be applied to tasks of supervised learning, like classification, in particular when such matrices are generated by data of different dimensionality (e. g. time series with same number of variables but different time sampling).

EEG Electroencephalogram (EEG) +3

Circumventing the Curse of Dimensionality in Magnetic Resonance Fingerprinting through a Deep Learning Approach

1 code implementation28 Nov 2018 Marco Barbieri, Leonardo Brizi, Enrico Giampieri, Francesco Solera, Gastone Castellani, Claudia Testa, Daniel Remondini

Results demonstrated that training with random sampling and different levels of noise variance yielded the best performance.

Medical Physics

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