3 papers
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.ME2026
Nonlinear Probabilistic Forecast Reconciliation
Anubhab Biswas, Lorenzo Zambon, Lorenzo Nespoli +1
Forecast reconciliation adjusts independently generated forecasts so that they satisfy some known constraints. While probabilistic forecast reconciliation is well established for l…
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…