Supervisor: Matteo Fontana

Conformal Binning is a technique, inspired to traditional Conformal Prediction, and very recently proposed in the literature (https://arxiv.org/html/2503.03841v1) which involves partitioning the data into bins based on certain characteristics, such as the range of predicted values or difficulty estimates. Separate prediction intervals are then constructed for each bin, tailored to the specific distribution of data … full description “Exploring Partitioning for Conformal Binning Strategies (available)”