Time Series Forecasting, Classification, Deep Learning, Recurrent Neural Network, Missing Data.
general deep model to handle missing data in time-series datasets. 2. A great answer to characterize the missing patterns of not complete-missed at random in the dataset set with masking and intervals. 3. A great manner of studying the effect of variable missingness on prediction labels by decay