An improved self-attention for long-sequence time-series data forecasting with missing values

Long-sequence time-series data forecasting based on deep learning has been applied in many practical scenarios. However, the time-series data sequences obtained in the real world inevitably contain missing values due to the failures of sensors or network fluctuations. Current research works dedicate...

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