SBI

CP4SBI is a conformal calibration framework for simulation-based inference: it recalibrates posterior credible sets from neural estimators to guarantee local Bayesian coverage. Two variants, based on regression trees and on CDFs, give finite-sample guarantees and substantially improve uncertainty quantification for estimators built with normalizing flows and diffusion models.