TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting
Abstract
Real-world time series inherently exhibit significant non-stationarity, posing substantial challenges for forecasting. To address this issue, this paper proposes a novel prediction framework, TimeStacker, designed to overcome the limitations of existing models in capturing the characteristics of non-stationary signals. By employing a unique stacking mechanism, TimeStacker effectively captures global signal features while thoroughly exploring local details. Furthermore, the framework integrates a frequency-based self-attention module, significantly enhancing its feature modeling capabilities. Experimental results demonstrate that TimeStacker achieves outstanding performance across multiple real-world datasets, including those from the energy, finance, and weather domains. It not only delivers superior predictive accuracy but also exhibits remarkable advantages with fewer parameters and higher computational efficiency.
Cite
Text
Liu et al. "TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting." Proceedings of the 42nd International Conference on Machine Learning, 2025.Markdown
[Liu et al. "TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting." Proceedings of the 42nd International Conference on Machine Learning, 2025.](https://mlanthology.org/icml/2025/liu2025icml-timestacker/)BibTeX
@inproceedings{liu2025icml-timestacker,
title = {{TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting}},
author = {Liu, Qinglong and Xu, Cong and Jiang, Wenhao and Wang, Kaixuan and Ma, Lin and Li, Haifeng},
booktitle = {Proceedings of the 42nd International Conference on Machine Learning},
year = {2025},
pages = {39929-39946},
volume = {267},
url = {https://mlanthology.org/icml/2025/liu2025icml-timestacker/}
}