Preprint Open access
Adaptive Conformal Prediction for Image Regression Models with Application to an Inertial Confinement Fusion Emulator
Uncertainty quantification is critical in scientific machine learning, where black-box, image-based models are increasingly deployed in high-stakes settings. In many such applications, model outputs inform costly decisions, yet most methods provide only point estimates without quantifying predictive uncertainty. This c …