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cs.LG2026
Learning to Forecast on Multiple Spatiotemporal Hierarchies
Valentina Moretti, Cesare Alippi, Andrea Cini
Hierarchical forecasting exploits aggregation structures that expose multiple views of the same underlying spatiotemporal forecasting problem, while ensuring coherence among foreca…
cs.LG2025
Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting
Valentina Moretti, Ivan Marisca, Cesare Alippi +1
Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contradictory empirical results make…