A hard problem indeed. The methods in your list have use different settings. Deep Ensembles, MC Dropout don't require a calibration set. The prior networks (i love this paper) assume that during training OOD samples are available. Conformal prediction assumes the availability of a calibration set that follows the distribution of future data... For the other methods,I would have to check ...