Transductive LSTM for Time-Series Prediction: an Application to Weather Forecasting KU Leuven
Long Short-Term Memory (LSTM) has shown significant performance on many real-world applications due to its ability to capture long-term dependencies. In this paper, we utilize LSTM to obtain a data-driven forecasting model for an application of weather forecasting. Moreover, we propose Transductive LSTM (T-LSTM) which exploits the local information in time-series prediction. In transductive learning, the samples in the test point vicinity are ...