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stat.ML2026
Model selection with proper scoring rules on data sets of time series: prefer the mean scaled score
Giorgio Corani, Stefano Damato, Dario Azzimonti +1
We study the problem of model selection among probabilistic forecasting models evaluated on datasets of multiple time series. The performance of a model on a single time series is…
stat.ML2026
Intermittent time series forecasting: local vs global models
Stefano Damato, Nicolò Rubattu, Dario Azzimonti +1
Forecasting intermittent time series, which contain zeros, is a crucial challenge in supply chains as inventory policies require probabilistic forecasts to establish safety levels.…
stat.ML2025
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood
Stefano Damato, Dario Azzimonti, Giorgio Corani
We adopt Gaussian Processes (GPs) as latent functions for probabilistic forecasting of intermittent time series. The model is trained in a Bayesian framework that accounts for the…