Papers › HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling for Long-Term Forecasting
HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling for Long-Term Forecasting
Shubao Zhao, Ming Jin, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Qingsong Wen, Yi Wang
Time series forecasting is crucial and challenging in the real world. The recent surge in interest regarding time series foundation models, which cater to a diverse array of downstream tasks, is noteworthy. However, existing methods often overlook the multi-scale nature of time series, an aspect crucial for precise forecasting. To bridge this gap, we propose HiMTM, a hierarchical multi-scale masked time series modeling method designed for long-term forecasting. Specifically, it comprises four integral components: (1) hierarchical multi-scale transformer (HMT) to capture temporal information at different scales; (2) decoupled encoder-decoder (DED) forces the encoder to focus on feature extraction, while the decoder to focus on pretext tasks; (3) multi-scale masked reconstruction (MMR) provides multi-stage supervision signals for pre-training; (4) cross-scale attention fine-tuning (CSA-FT) to capture dependencies between different scales for forecasting. Collectively, these components enhance multi-scale feature extraction capabilities in masked time series modeling and contribute to improved prediction accuracy. We conduct extensive experiments on 7 mainstream datasets to prove that HiMTM has obvious advantages over contemporary self-supervised and end-to-end learning methods. The effectiveness of HiMTM is further showcased by its application in the industry of natural gas demand forecasting.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Time Series Forecasting | ETTh1 (336) Multivariate | HiMTM | MAE | 0.430 | #19 of 72 | Archive leaderboard | report |
| Time Series Forecasting | ETTh1 (336) Multivariate | HiMTM | MSE | 0.422 | #19 of 72 | Archive leaderboard | report |
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