Differentiable nonconformity scores induce flows that sample conformal prediction set boundaries, and mixing flows across levels produces conformal predictive distributions whose quantiles match the sets.
Fundamentals of digital image processing
2 Pith papers cite this work. Polarity classification is still indexing.
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Enhanced ProtoPNet delivers the highest faithfulness score of 0.1534 when explaining diffusion-based MRI synthesis compared to other prototype methods.
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Flow-Based Conformal Predictive Distributions
Differentiable nonconformity scores induce flows that sample conformal prediction set boundaries, and mixing flows across levels produces conformal predictive distributions whose quantiles match the sets.
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Explainability in Generative Medical Diffusion Models: A Faithfulness-Based Analysis on MRI Synthesis
Enhanced ProtoPNet delivers the highest faithfulness score of 0.1534 when explaining diffusion-based MRI synthesis compared to other prototype methods.