TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
June 27, 2025 ยท View on GitHub
๐ฐ News
๐ฉ 2025-05-01: TimeFilter has been accepted as ICML 2025 Poster.
๐ฉ 2025-01-22: Initial upload to arXiv PDF.
๐ Overview
TimeFilter is a cutting-edge solution for time series forecasting, incorporating three main components: the Spatial-Temporal Construction Module, the Patch-Specific Filtration Module, and the Adaptive Graph Learning Module.

๐ Prerequisites
Ensure you are using Python 3.10.16 and install the necessary dependencies by running:
pip install -r requirements.txt
๐ Prepare Datastes
Begin by downloading the required datasets. All datasets are conveniently available at iTransformer. Create a separate folder named ./data and neatly organize all the csv files as shown below:
data
โโโ electricity.csv
โโโ ETTh1.csv
โโโ ETTh2.csv
โโโ ETTm1.csv
โโโ ETTm2.csv
โโโ traffic.csv
โโโ weather.csv
โโโ solar_AL.txt
โโโ PEMS03.npz
โโโ PEMS04.npz
โโโ PEMS07.npz
โโโ PEMS08.npz
๐ป Training
All scripts are located in ./scripts. For instance, to train a model using the ETTh1 dataset with an input length of 96, simply run:
bash ./scripts/ETTh1.sh
After training:
- Your trained model will be safely stored in
./checkpoints. - Numerical results in .npy format can be found in
./results. - A comprehensive summary of quantitative metrics is accessible in
./result_long_term_forecast.txt.
๐ Citation
If you find this repo useful, please consider citing our paper as follows:
@inproceedings{
hu2025timefilter,
title={TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting},
author={Yifan Hu and Guibin Zhang and Peiyuan Liu and Disen Lan and Naiqi Li and Dawei Cheng and Tao Dai and Shu-Tao Xia and Shirui Pan},
booktitle={Forty-second International Conference on Machine Learning},
year={2025},
url={https://openreview.net/forum?id=490VcNtjh7}
}
๐ Acknowledgement
Special thanks to the following repositories for their invaluable code and datasets:
๐ฉ Contact
If you have any questions, please contact huyf0122@gmail.com or submit an issue.