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cs.LG2025
ReCast: Reliability-aware Codebook Assisted Lightweight Time Series Forecasting
Xiang Ma, Taihua Chen, Pengcheng Wang +2
Time series forecasting is crucial for applications in various domains. Conventional methods often rely on global decomposition into trend, seasonal, and residual components, which…
cs.LG2024★ 1 cited
U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
Xiang Ma, Xuemei Li, Lexin Fang +2
Time series forecasting is a crucial task in various domains. Caused by factors such as trends, seasonality, or irregular fluctuations, time series often exhibits non-stationary. I…
cs.LG2023★ 2 cited
MPR-Net:Multi-Scale Pattern Reproduction Guided Universality Time Series Interpretable Forecasting
Tianlong Zhao, Xiang Ma, Xuemei Li +1
Time series forecasting has received wide interest from existing research due to its broad applications and inherent challenging. The research challenge lies in identifying effecti…