Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators

31 January 2024

Papers citing "Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators"

8 / 8 papers shown

Title
FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecasting Y. Wang Y. Liu Xiaoyi Duan Kai Wang AI4TS 24 0 0 07 May 2025
Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Chengsen Wang Q. Qi J. Wang Haifeng Sun Zirui Zhuang J. Liao AI4TS 42 0 0 01 May 2025
ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecasting Guoqi Yu Yaoming Li Juncheng Wang Xiaoyu Guo Angelica I. Aviles-Rivero Tong Yang Shujun Wang AI4TS 44 0 0 24 Feb 2025
Are Language Models Actually Useful for Time Series Forecasting? Mingtian Tan Mike A. Merrill Vinayak Gupta Tim Althoff Thomas Hartvigsen AI4TS 39 44 0 22 Jun 2024
DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting Yuxuan Shu Vasileios Lampos AI4TS AI4CE 55 0 0 11 Jun 2024
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting Kun Yi Qi Zhang Wei Fan Shoujin Wang Pengyang Wang Hui He Defu Lian Ning An Longbin Cao ZhenDong Niu AI4TS 56 120 0 10 Nov 2023
Long-Range Transformers for Dynamic Spatiotemporal Forecasting J. E. Grigsby Zhe Wang Nam Nguyen Yanjun Qi AI4TS 58 83 0 24 Sep 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 164 3,799 0 14 Dec 2020