Recent Advances in Conformal Prediction with E-Values

par Etienne Gauthier (Inria & ENS)

mardi 10 févr. 2026, 11:15 → 12:15 Europe/Paris

Salle K. Johnson (1R3, 1er étage)

Conformal prediction has become a versatile framework for distribution-free uncertainty quantification, offering coverage guarantees under minimal assumptions. Traditionally, these methods rely on p-values to ensure marginal coverage when all data are exchangeable. More recently, e-values have emerged as a powerful and flexible tool in statistics. Their integration into conformal prediction has opened the door to constructing valid prediction sets in more complex and challenging settings. In this talk, I will provide an overview of these advances, explain the key ideas behind using e-values in conformal prediction, and highlight examples that demonstrate both their promise and the open questions they raise.