SimTS_Representation_Learning

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SimTS_Representation_Learning

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# SimTS: A PyTorch Implementation

This is a PyTorch implementation of the paper [SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting](https://arxiv.org/abs/2303.18205):
```
@Article{SimTS2023,
    title={SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting},
    author={Zheng, Xiaochen and Chen, Xingyu and Sch{\"u}rch, Manuel and Mollaysa, Amina and Allam, Ahmed and Krauthammer, Michael},
    journal={arXiv preprint arXiv:2303.18205},
    year={2023}
}
```
# News
* Apr 19, 2023: Added hierarchical temporal loss from [TS2Vec](https://arxiv.org/abs/2106.10466). Many thanks to [Alexander März](https://github.com/StatMixedML)! 
* Apr 11, 2023: Released codes for SimTS.

<details>
 <summary>More News</summary>
 
 <ul>
 <li>Jun 30, 1905: Albert Einstein published the theory of special relativity in Annalen der Physik. </li>
 </ul>
 
</details>

# Setup
## Dependencies
A list of dependencies is provided in ```requirements.txt```. After creating a virtual environment, we recommend installing dependencies via ```pip```:

```shell
pip install -r /path/to/requirements.txt
```
## Dataset
Benchmark datasets can be downloaded [here](https://drive.google.com/drive/folders/1ZOYpTUa82_jCcxIdTmyr0LXQfvaM9vIy?usp=sharing).

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