5 citations · 6 across the 5 of their papers we have counts for
5 papers
Estimating effective connectivity in linear brain network models
Giulia Prando, Mattia Zorzi, Alessandra Bertoldo +1
Contemporary neuroscience has embraced network science to study the complex and self-organized structure of the human brain; one of the main outstanding issues is that of inferring…
The Harmonic Analysis of Kernel Functions
Mattia Zorzi, Alessandro Chiuso
Kernel-based methods have been recently introduced for linear system identification as an alternative to parametric prediction error methods. Adopting the Bayesian perspective, the…
Classical vs. Bayesian methods for linear system identification: point estimators and confidence sets
D. Romeres, G. Prando, G. Pillonetto +1
This paper compares classical parametric methods with recently developed Bayesian methods for system identification. A Full Bayes solution is considered together with one of the st…
Identification of stable models via nonparametric prediction error methods
Diego Romeres, Gianluigi Pillonetto, Alessandro Chiuso
A new Bayesian approach to linear system identification has been proposed in a series of recent papers. The main idea is to frame linear system identification as predictor estimati…
Convex vs nonconvex approaches for sparse estimation: GLasso, Multiple Kernel Learning and Hyperparameter GLasso
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso +1
The popular Lasso approach for sparse estimation can be derived via marginalization of a joint density associated with a particular stochastic model. A different marginalization of…