Papers
Demand Forecasting & Inventory Management
N-BEATS: 11% Improvement in Time Series Forecasting
The N-BEATS architecture, proposed by Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, and Yoshua Bengio, demonstrates that pure deep learning can outperform classical statistical methods in time series forecasting. The model, which is both interpretable and generic, achieved a 11% improvement over the statistical benchmark on M4 datasets.