Search Results for author: Yiduo Li

Found 5 papers, 2 papers with code

Enhancing Multivariate Time Series Forecasting with Mutual Information-driven Cross-Variable and Temporal Modeling

no code implementations1 Mar 2024 shiyi qi, Liangjian Wen, Yiduo Li, Yuanhang Yang, Zhe Li, Zhongwen Rao, Lujia Pan, Zenglin Xu

To substantiate this claim, we introduce the Cross-variable Decorrelation Aware feature Modeling (CDAM) for Channel-mixing approaches, aiming to refine Channel-mixing by minimizing redundant information between channels while enhancing relevant mutual information.

Multivariate Time Series Forecasting Time Series

PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations

no code implementations25 Feb 2024 shiyi qi, Zenglin Xu, Yiduo Li, Liangjian Wen, Qingsong Wen, Qifan Wang, Yuan Qi

Recent advancements in deep learning have led to the development of various models for long-term multivariate time-series forecasting (LMTF), many of which have shown promising results.

Multivariate Time Series Forecasting Time Series

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

1 code implementation18 May 2023 Zhe Li, shiyi qi, Yiduo Li, Zenglin Xu

In this paper, we thoroughly investigate the intrinsic effectiveness of recent approaches and make three key observations: 1) linear mapping is critical to prior long-term time series forecasting efforts; 2) RevIN (reversible normalization) and CI (Channel Independent) play a vital role in improving overall forecasting performance; and 3) linear mapping can effectively capture periodic features in time series and has robustness for different periods across channels when increasing the input horizon.

Time Series Time Series Forecasting

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