pip install -r requirements.txt
The datasets can be obtained from here.
# ECL
bash ./scripts/multivariate_forecasting/ECL/S_Mamba.sh
# Exchange
bash ./scripts/multivariate_forecasting/Exchange/S_Mamba.sh
# Traffic
bash ./scripts/multivariate_forecasting/Traffic/S_Mamba.sh
# Weather
bash ./scripts/multivariate_forecasting/Weather/S_Mamba.sh
# Solar-Energy
bash ./scripts/multivariate_forecasting/SolarEnergy/S_Mamba.sh
# PEMS
bash ./scripts/multivariate_forecasting/PEMS/S_Mamba_03.sh
bash ./scripts/multivariate_forecasting/PEMS/S_Mamba_04.sh
bash ./scripts/multivariate_forecasting/PEMS/S_Mamba_07.sh
bash ./scripts/multivariate_forecasting/PEMS/S_Mamba_08.sh
# ETT
bash ./scripts/multivariate_forecasting/ETT/S_Mamba_ETTm1.sh
bash ./scripts/multivariate_forecasting/ETT/S_Mamba_ETTm2.sh
bash ./scripts/multivariate_forecasting/ETT/S_Mamba_ETTh1.sh
bash ./scripts/multivariate_forecasting/ETT/S_Mamba_ETTh2.sh
We are grateful for the following awesome projects when implementing S-Mamba:
If you find our work useful in your research, please consider citing us:
@article{wang2024mamba,
title={Is Mamba Effective for Time Series Forecasting?},
author={Wang, Zihan and Kong, Fanheng and Feng, Shi and Wang, Ming and Zhao, Han and Wang, Daling and Zhang, Yifei},
journal={arXiv preprint arXiv:2403.11144},
year={2024}
}