Conformal regression provides prediction intervals with global coverage guarantees, but
often fails to capture local error distributions, leading to non-homogeneous coverage. We …

Conformal prediction, and split conformal prediction as a specific implementation, offer a
distribution-free approach to estimating prediction intervals with statistical guarantees …

This paper introduces Conformal Thresholded Intervals (CTI), a novel conformal regression
method that aims to produce the smallest possible prediction set with guaranteed coverage …

Conformal Prediction methods have finite-sample distribution-free marginal coverage
guarantees. However, they generally do not offer conditional coverage guarantees, which …

We compare two recent methods that combine conformal inference with quantile regression
to produce locally adaptive and marginally valid prediction intervals under sample …

Conformal prediction is a technique for constructing prediction intervals that attain valid
coverage in finite samples, without making distributional assumptions. Despite this appeal …

When one observes a sequence of variables $(x_1, y_1),\ldots,(x_n, y_n) $, Conformal
Prediction (CP) is a methodology that allows to estimate a confidence set for $ y_ {n+ 1} …

We propose a new inference framework called localized conformal prediction. It generalizes
the framework of conformal prediction by offering a single-test-sample adaptive construction …

Conformal inference is a popular tool for constructing prediction intervals. We consider here
the scenario of post-selection/selective conformal inference, that is, prediction intervals are …

Training-conditional coverage guarantees in conformal prediction concern the concentration
of the error distribution, conditional on the training data, below some nominal level. The …