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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.LG2025★ 3 cited

Multivariate Forecasting of Bitcoin Volatility with Gradient Boosting: Deterministic, Probabilistic, and Feature Importance Perspectives

Grzegorz Dudek, Mateusz Kasprzyk, Paweł Pełka

This study investigates the application of the Light Gradient Boosting Machine (LGBM) model for both deterministic and probabilistic forecasting of Bitcoin realized volatility. Uti…

cs.LG2025★ 2 cited

Forecasting Cryptocurrency Prices using Contextual ES-adRNN with Exogenous Variables

Slawek Smyl, Grzegorz Dudek, Paweł Pełka

In this paper, we introduce a new approach to multivariate forecasting cryptocurrency prices using a hybrid contextual model combining exponential smoothing (ES) and recurrent neur…