Rafael Izbicki
Rafael Izbicki
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Conformal Predictions
CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference
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.
L. M. C. Cabezas
,
V. S. Santos
,
T. R. Ramos
,
P. L. C. Rodrigues
,
Rafael Izbicki
April, 2026
Philosophical Transactions of the Royal Society A
Preprint
Conformal Calibration of Statistical Confidence Sets
L. M. C. Cabezas
,
G. P. Soares
,
T. R. Ramos
,
R. B. Stern
,
Rafael Izbicki
April, 2026
Transactions on Machine Learning Research
PDF
Regression Trees for Fast and Adaptive Prediction Intervals
L. M. C. Cabezas
,
M. P. Otto
,
Rafael Izbicki
,
R. B. Stern
February, 2025
Information Sciences
Preprint
PDF
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