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Uncertainty quantification for inverse problems in imaging has drawn much attention lately.
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Roger Koenker and Gilbert Bassett Jr · 1978
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Orthonormal wavelets
Yves Meyer · 1990
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Deep unsupervised learning using nonequilibrium thermodynamics
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Distribution-free, risk-controlling prediction sets
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Image-to-image regression with distribution-free uncertainty quantification and applications in imaging
Anastasios N Angelopoulos, Amit Pal Kohli, Stephen Bates, Michael Jordan, Jitendra Malik, Thayer Alshaabi, Srigokul Upadhyayula, and Yaniv Romano · 2022
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Semantic uncertainty intervals for disentangled latent spaces
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Cascaded diffusion models for high fidelity image generation
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Distributional conformal prediction
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Image super-resolution via iterative refinement
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Nested conformal prediction and quantile out-of-bag ensemble methods
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Learning multi-scale local conditional probability models of images
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