SeriesGAN implementation in pytorch

Adapts the original SeriesGAN code using pytorch. Also significantly speeds up the training process.

Instructions for training the model

If you have uv installed (recommended):

git clone https://github.com/NiekDrenth/SeriesGAN-pytorch.git
cd SeriesGAN-pytorch
uv sync
uv run train.py

Without uv:

git clone https://github.com/NiekDrenth/SeriesGAN-pytorch.git
cd SeriesGAN-pytorch

Make sure you have python 3.13 Create a virtual environment

python3.13 -m venv .venv

activate it

Mac/Linux:

source .venv/bin/activate

Windows:

.\venv\Scripts\Activate.ps1

Install requirements and run:

pip install -r requirements.txt
python train.py

How to Cite

Please Cite the original authors of the paper. The paper associated with this repository has been accepted at BigData 2024 as a regular paper for oral presentation. We kindly ask you to provide a citation to acknowledge our work.

Available on arXiv: https://arxiv.org/abs/2410.21203

Here is the BibTeX citation for your reference:

@misc{eskandarinasab2024seriesgan,
     title={SeriesGAN: Time Series Generation via Adversarial and Autoregressive Learning}, 
     author={MohammadReza EskandariNasab and Shah Muhammad Hamdi and Soukaina Filali Boubrahimi},
     year={2024},
     eprint={2410.21203},
     archivePrefix={arXiv},
     primaryClass={cs.LG},
     url={https://arxiv.org/abs/2410.21203}, 
}