A selective inference framework is proposed to provide p-values controlling false positive rates for diffusion-based anomaly localization in images.
Quantifying statistical significance of neural network-based image segmentation by selective inference
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Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference
A selective inference framework is proposed to provide p-values controlling false positive rates for diffusion-based anomaly localization in images.