Official implementation of the work Sequential Predictive Conformal Inference for Time Series (ICML 2023). Slide and Poster are also available.
Please direct questions regarding implementation to [email protected].
See tutorial_electric_EnbPI_SPCI.ipynb for comparing SPCI against EnbPI, which is an earlier method of ours. We demonstrate significant reduction in interval width on the electric dataset, which is also used in Nex-CP (Barber et al., 2022).
Installation of dependency:
pip install -r requirements.txt
If you find our work useful, please consider citing it.
@InProceedings{xu2023SPCI,
title = {Sequential Predictive Conformal Inference for Time Series},
author = {Xu, Chen and Xie, Yao},
booktitle = {Proceedings of the 40th International Conference on Machine Learning},
pages = {38707--38727},
year = {2023},
editor = {Krause, Andreas and Brunskill, Emma and Cho, Kyunghyun and Engelhardt, Barbara and Sabato, Sivan and Scarlett, Jonathan},
volume = {202},
series = {Proceedings of Machine Learning Research},
month = {23--29 Jul},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v202/xu23r/xu23r.pdf},
url = {https://proceedings.mlr.press/v202/xu23r.html}
}