Hi @Kevin-Chen0,
Thank you for your comment. Indeed, I think this could be a valuable addition to MAPIE. For the moment, we have focused our efforts in Time Series on the following papers (#334):

• Gibbs, I., & Candes, E. (2021). Adaptive conformal inference under distribution shift. Advances in Neural Information Processing Systems, 34, 1660-1672.
• Zaffran, M., Féron, O., Goude, Y., Josse, J., & Dieuleveut, A. (2022, June). Adaptive conformal predictions for time series. In International Conference on Machine Learning (pp. 25834-25866). PMLR.

If you want to contribute to the library, I think this could be a very interesting new addition!
Don't hesitate to contact us if you have any questions regarding the how and where to implement this method.

Hi @LacombeLouis,

Yes, I can contribute to MAPIE by adding SCPI there. Will you also be including ACI in MapieTimeSeriesRegressor? That way, we can ensure I follow the same structure when incorporating SCPI.

Thanks!
~Kevin

Hi @Kevin-Chen0,

Indeed, we are including it at this very moment, it's in the final stages of development... 🔜 #341.

I think that as soon as it's released, we will make sure to keep you posted!
Thank you!
Louis

Hi @Kevin-Chen0, Thank you for your comment. Indeed, I think this could be a valuable addition to MAPIE. For the moment, we have focused our efforts in Time Series on the following papers (#334):

• Gibbs, I., & Candes, E. (2021). Adaptive conformal inference under distribution shift. Advances in Neural Information Processing Systems, 34, 1660-1672.
• Zaffran, M., Féron, O., Goude, Y., Josse, J., & Dieuleveut, A. (2022, June). Adaptive conformal predictions for time series. In International Conference on Machine Learning (pp. 25834-25866). PMLR.

If you want to contribute to the library, I think this could be a very interesting new addition! Don't hesitate to contact us if you have any questions regarding the how and where to implement this method.

I think SPCI outperforms these methods as who's in SPCI paper?