155 citations · 313 across the 15 of their papers we have counts for
16 papers
Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies
Nicolò Rubattu, Gabriele Maroni, Giorgio Corani
We describe our experience in developing a predictive model that placed high position in the BigDeal Challenge 2022, an energy competition of load and peak forecasting. We present…
Efficient probabilistic reconciliation of forecasts for real-valued and count time series
Lorenzo Zambon, Dario Azzimonti, Giorgio Corani
Hierarchical time series are common in several applied fields. The forecasts for these time series are required to be coherent, that is, to satisfy the constraints given by the hie…
Probabilistic Reconciliation of Count Time Series
Giorgio Corani, Dario Azzimonti, Nicolò Rubattu
Forecast reconciliation is an important research topic. Yet, there is currently neither formal framework nor practical method for the probabilistic reconciliation of count time ser…
Time series forecasting with Gaussian Processes needs priors
Giorgio Corani, Alessio Benavoli, Marco Zaffalon
Automatic forecasting is the task of receiving a time series and returning a forecast for the next time steps without any human intervention. Gaussian Processes (GPs) are a powerfu…
A Bayesian Hierarchical Score for Structure Learning from Related Data Sets
Laura Azzimonti, Giorgio Corani, Marco Scutari
Score functions for learning the structure of Bayesian networks in the literature assume that data are a homogeneous set of observations; whereas it is often the case that they com…
Reconciling Hierarchical Forecasts via Bayes' Rule
Giorgio Corani, Dario Azzimonti, João P. S. C. Augusto +1
We present a novel approach for reconciling hierarchical forecasts, based on Bayes rule. We define a prior distribution for the bottom time series of the hierarchy, based on the bo…