Abstract: Time-series forecasting plays a pivotal role in decision-making. Recently, as deep learning models have shown exceptional performance in time-series forecasting, research in the field of ...
Abstract: This paper introduces SparseTSF, a novel and extremely lightweight method for Long-term Time Series Forecasting (LTSF), designed to address the challenges of modeling complex temporal ...
Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.
A) Retail/E-commerce inventory (forecasting product demand for stores or online sales) B) Manufacturing raw materials (forecasting material needs for production) C) Distribution/logistics (forecasting ...
ICLR 2022 https://openreview.net/group?id=ICLR.cc/2022/Conference Oct 06 '21 Jan 24 '22 ICLR 2021 https://openreview.net/group?id=ICLR.cc/2021/Conference ICLR 2020 ...
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