The code repository for paper: "iTFKAN: Interpretable Time Series Forecasting with Kolmogorov–Arnold Network"
- Install Python 3.8. For convenience, execute the following command.
pip install -r requirements.txt
-
Prepare Data. You can obtain the well pre-processed datasets from [Google Drive] or [Baidu Drive], Then place the downloaded data in the folder
./dataset. -
Train and evaluate model.
# long-term forecast
bash ./scripts/long_term_forecast/ETT_script/MultiDomainFourierKAN_ETTh1.sh
# short-term forecast
bash ./scripts/short_term_forecast/MultiDomainFourierKAN_M4.sh
@inproceedings{wu2023timesnet, title={TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis}, author={Haixu Wu and Tengge Hu and Yong Liu and Hang Zhou and Jianmin Wang and Mingsheng Long}, booktitle={International Conference on Learning Representations}, year={2023}, }