Welcome to the official codebase of TimeDRL.
This project is based on research that has been accepted for publication at the International Conference on Data Engineering (ICDE) 2024.
requirements.txt
to install the dependencies
pip install -r requirements.txt
python main.py --...
Alternatively, if you prefer to use locally defined parameters to overwrite args for faster experimentation iterations, run:
python main.py --overwrite_args
exp_settings_and_results
to see all the experiments' settings and corresponding results.If you find value in this repository, we kindly ask that you cite our paper.
@article{chang2023timedrl,
title={TimeDRL: Disentangled Representation Learning for Multivariate Time-Series},
author={Chang, Ching and Chan, Chiao-Tung and Wang, Wei-Yao and Peng, Wen-Chih and Chen, Tien-Fu},
journal={arXiv preprint arXiv:2312.04142},
year={2023}
}
If you have any questions or suggestions, please reach out to Ching Chang at blacksnail789521@gmail.com, or raise them in the 'Issues' section.
This library was built upon the following repositories: