References#

[Duchemin2025]

Duchemin Q. and Obozinski G. (2025). Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts.

[Bhat2015]

Bhat, H.S. and al (2015). Towards scalable quantile regression trees.

[Romano2019]

Romano, Y., Patterson, E., and Candes, E. (2019). Conformalized Quantile Regression.

[Angelopoulos2021]

Angelopoulos, A. and Bates, S. (2021). Distribution-free uncertainty quantification for deep learning.

[Gneiting2007]

Gneiting, T. and Raftery, A.E. (2007). * Evaluating epidemic forecasts in an interval format*