https://github.com/adityalab/pets
https://github.com/adityalab/pets
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/adityalab/pets
- Owner: AdityaLab
- Created: 2023-10-09T18:25:34.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-29T19:16:04.000Z (over 2 years ago)
- Last Synced: 2023-10-29T20:30:09.615Z (over 2 years ago)
- Language: Python
- Size: 485 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Performative Time-Series Forecasting
## Publication
Implementation of the paper "Performative Time-Series Forecasting."
Authors: Leo Zhiyuan Zhao, Alexander Rodríguez, B.Aditya Prakash
Paper + Appendix: [https://arxiv.org/abs/2310.06077](https://arxiv.org/abs/2310.06077)
## Training
METR-LA Dataset download link: [https://zenodo.org/record/5146275/files/METR-LA.csv?download=1](https://zenodo.org/record/5146275/files/METR-LA.csv?download=1)
Example to run the covid dataset:
```
python3 run_covid.py --seed 0 --dev cuda:0 --model rnn --fps 0
```
Example to run the metrla dataset:
```
python3 run_metrla.py --seed 0 --dev cuda:0 --model rnn --fps 0
```
Example to run the metrla dataset out-of-distribution test:
```
python3 run_metrla_ood.py --seed 0 --dev cuda:0 --model rnn --fps 0
```
Implemented Models: ```{rnn, lstnet, transformer, informer}```
```fps=0``` is running conventional forecasting models, ```fps=1``` is running fps.
## Contact
If you have any questions about the code, please contact Leo Zhiyuan Zhao at ```leozhao1997[at]gatech[dot]edu```.
## Citation
If you find our work useful, please cite our work:
```
@article{zhao2023performative,
title={Performative Time-Series Forecasting},
author={Zhao, Zhiyuan and Rodriguez, Alexander and Prakash, B Aditya},
journal={arXiv preprint arXiv:2310.06077},
year={2023}
}
```