Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

Conformalized matrix completion

An Independence Test based on Data-Driven Tree-Structured Representations.

Example on task completion times stressing the importance of distribution-free intervals, as well as .py file containing code to calculate such intervals.

Distribution-free test for general differences in two populations

A method for cold-deck imputation of a continuous distribution from binned incomes, using a real-world reference data set

ConformalLab — Interactive Conformal Prediction & Distribution-Free Inference Laboratory. 6 modules: split conformal, ACI, classification sets, coverage guarantees, CQR, Mondrian CP. Zero dependencies.

A distribution-free conformal prediction certification layer for safety-critical ordinal classification. Guarantees contiguous prediction sets, marginal/group-conditional validity, true-label coverage under banded reporting noise, and severity-weighted risk control (fatal-omission bounds) with an explicit additive slack budget.