FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. (arXiv:2205.08897v1 [cs.LG])

Recent studies have shown the promising performance of deep learning models
(e.g., RNN and Transformer) for long-term time series forecasting. These
studies mostly focus on designing deep models to effectively combine historical
information for long-term forecasting. However, the question of how to
effectively represent historical information for long-term forecasting has not
received enough attention, limiting our capacity to exploit powerful deep
learning models. The main challenge in time series representation is how to
handle the dilemma between accurately preserving historical …

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