6 citations · 35 across the 20 of their papers we have counts for
21 papers
Scalable Variational Bayes Inference for Dynamic Variable Selection
Nicolas Bianco, Mauro Bernardi, Daniele Bianchi
We develop a variational Bayes approach for dynamic variable selection in high-dimensional regression models with time-varying parameters and predictors that exhibit a predefined g…
Flexible variational approximations for stochastic volatility-managed portfolios
Nicolas Bianco, Mauro Bernardi
This paper investigates volatility-managed portfolios through a variational Bayes approach that smooths stochastic volatility forecasts. Our algorithm exhibits competitive performa…
Missing data patterns in runners' careers: do they matter?
Mattia Stival, Mauro Bernardi, Manuela Cattelan +1
Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a data set with annual seasona…
Doubly-online changepoint detection for monitoring health status during sports activities
Mattia Stival, Mauro Bernardi, Petros Dellaportas
We provide an online framework for analyzing data recorded by smart watches during running activities. In particular, we focus on identifying variations in the behavior of one or m…
Variational inference for large Bayesian vector autoregressions
Mauro Bernardi, Daniele Bianchi, Nicolas Bianco
We propose a novel variational Bayes approach to estimate high-dimensional vector autoregression (VAR) models with hierarchical shrinkage priors. Our approach does not rely on a co…
Locally Sparse Function on function Regression
Mauro Bernardi, Antonio Canale, Marco Stefanucci
In functional data analysis, functional linear regression has attracted significant attention recently. Herein, we consider the case where both the response and covariates are func…