33 citations · 38 across the 22 of their papers we have counts for
5 papers · 1 filter
Implementation paradigm for supervised flare forecasting studies: a deep learning application with video data
Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto +2
Solar flare forecasting can be realized by means of the analysis of magnetic data through artificial intelligence techniques. The aim is to predict whether a magnetic active region…
Prediction of severe thunderstorm events with ensemble deep learning and radar data
Sabrina Guastavino, Michele Piana, Marco Tizzi +5
The problem of nowcasting extreme weather events can be addressed by applying either numerical methods for the solution of dynamic model equations or data-driven artificial intelli…
Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions
Domenico Cicogna, Francesco Berrilli, Daniele Calchetti +6
Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable pre…
Score-oriented loss (SOL) functions
Francesco Marchetti, Sabrina Guastavino, Michele Piana +1
Loss functions engineering and the assessment of forecasting performances are two crucial and intertwined aspects of supervised machine learning. This paper focuses on binary class…
Bad and good errors: value-weighted skill scores in deep ensemble learning
Sabrina Guastavino, Michele Piana, Federico Benvenuto
In this paper we propose a novel approach to realize forecast verification. Specifically, we introduce a strategy for assessing the severity of forecast errors based on the evidenc…