https://github.com/adityalab/foil
https://github.com/adityalab/foil
Last synced: 28 days ago
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- Host: GitHub
- URL: https://github.com/adityalab/foil
- Owner: AdityaLab
- License: mit
- Created: 2024-06-02T20:44:01.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-07-25T06:43:43.000Z (9 months ago)
- Last Synced: 2024-07-25T13:54:59.073Z (9 months ago)
- Language: Python
- Size: 1.38 MB
- Stars: 17
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# FOIL (ICML2024)
### This is an offical implementation of FOIL: [Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning](https://arxiv.org/abs/2406.09130).
## Requirements
Dependencies can be installed using the following file:
newtimelib_environment.yml
## Dataset
You can obtain the well pre-processed datasets from [[Google Drive]](https://drive.google.com/drive/folders/13Cg1KYOlzM5C7K8gK8NfC-F3EYxkM3D2?usp=sharing) or [[Baidu Drive]](https://pan.baidu.com/s/1r3KhGd0Q9PJIUZdfEYoymg?pwd=i9iy), Then place the downloaded data in the folder`./dataset`
## Try out FOIL
Usecase
Run Raw Informer on ILI dataset with Pred_Len=4:
```bash
cd Informer-Raw
python ILI-Pred4.py
```
Run Informer with FOIL on ILI dataset with Pred_Len=4:
```bash
cd Informer+FOIL
python ILI-Pred4-0.py
python ILI-Pred4-1.py
```
* First Infer Envrionment; Second Learn Invariant Reperesentation
## Citation
If you find this repo useful, please cite our paper.
```
@inproceedings{
liu2024timeseries,
title={Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning},
author={haoxin liu and Harshavardhan Kamarthi and Lingkai Kong and Zhiyuan Zhao and Chao Zhang and B. Aditya Prakash},
booktitle={Forty-first International Conference on Machine Learning},
year={2024},
url={https://openreview.net/forum?id=SMUXPVKUBg}
}
```
## Contact
If you have any questions or suggestions, feel free to contact:
[email protected]
## Acknowledgement
This library is constructed based on the following repos:
https://github.com/zhouhaoyi/Informer2020/
https://github.com/thuml/Time-Series-Library/
https://github.com/ts-kim/RevIN