This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation".
Please install the packages in requirements.txt
python download.py physiopython download.py pm25Please put files in GoogleDrive to the "data" folder.
python exe_physio.py --testmissingratio [missing ratio] --nsample [number of samples]python exe_physio.py --modelfolder pretrained --testmissingratio [missing ratio] --nsample [number of samples]python exe_pm25.py --nsample [number of samples]python exe_forecasting.py --datatype electricity --nsample [number of samples]'visualize_examples.ipynb' is a notebook for visualizing results.
A part of the codes is based on BRITS and DiffWave
If you use this code for your research, please cite our paper:
@inproceedings{tashiro2021csdi,
title={CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation},
author={Tashiro, Yusuke and Song, Jiaming and Song, Yang and Ermon, Stefano},
booktitle={Advances in Neural Information Processing Systems},
year={2021}
}