Applying the quantile check loss to BD-LSTM, ED-LSTM, and Conv-LSTM gives multi-step forecasts with 5th-95th percentile bands at similar RMSE to the standard models on crypto and benchmark data.
Waldmann, Quantile regression: A short story on how and why, Sta- tistical Modelling 18 (3-4) (2018) 203–218
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Quantile deep learning models for multi-step ahead time series prediction
Applying the quantile check loss to BD-LSTM, ED-LSTM, and Conv-LSTM gives multi-step forecasts with 5th-95th percentile bands at similar RMSE to the standard models on crypto and benchmark data.