7 citations · 11 across the 9 of their papers we have counts for
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Km-scale dynamical downscaling through conformalized latent diffusion models
Alessandro Brusaferri, Andrea Ballarino
Dynamical downscaling is crucial for deriving high-resolution meteorological fields from coarse-scale simulations, enabling detailed analysis for critical applications such as weat…
From Distributional to Quantile Neural Basis Models: the case of Electricity Price Forecasting
Alessandro Brusaferri, Danial Ramin, Andrea Ballarino
While neural networks are achieving high predictive accuracy in multi-horizon probabilistic forecasting, understanding the underlying mechanisms that lead to feature-conditioned ou…
NBMLSS: probabilistic forecasting of electricity prices via Neural Basis Models for Location Scale and Shape
Alessandro Brusaferri, Danial Ramin, Andrea Ballarino
Forecasters using flexible neural networks (NN) in multi-horizon distributional regression setups often struggle to gain detailed insights into the underlying mechanisms that lead…
On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices
Alessandro Brusaferri, Andrea Ballarino, Luigi Grossi +1
Probabilistic electricity price forecasting (PEPF) is subject of increasing interest, following the demand for proper quantification of prediction uncertainty, to support the opera…