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20202026
most citedES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting

7 citations · 19 across the 13 of their papers we have counts for

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cs.LG2024★ 1 cited

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting

Mateusz Kasprzyk, Paweł Pełka, Boris N. Oreshkin +1

This paper presents an enhanced N-BEATS model, N-BEATS*, for improved mid-term electricity load forecasting (MTLF). Building on the strengths of the original N-BEATS architecture,…

cs.LG2024

Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand

Slawek Smyl, Boris N. Oreshkin, Paweł Pełka +1

Power systems operate under uncertainty originating from multiple factors that are impossible to account for deterministically. Distributional forecasting is used to control and mi…