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Meaningful uncertainty quantification in computer vision requires reasoning about semantic information -- say, the hair color of the person in a photo or the location of a car on the street.
Regression quantiles
Roger Koenker and Gilbert Bassett Jr · 1978
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Probal Chaudhuri · 1991
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Roger Koenker and Kevin F Hallock · 2001
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Deep residual learning for image recognition
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CLEVR: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, and Ross B. Girshick · 2017
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Roger Koenker · 2017
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Dmitry Ulyanov, Andrea Vedaldi, and Victor S. Lempitsky · 2017
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The unreasonable effectiveness of deep features as a perceptual metric
PULSE: self-supervised photo upsampling via latent space exploration of generative models
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Classification with valid and adaptive coverage
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In-domain GAN inversion for real image editing
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A gentle introduction to conformal prediction and distribution-free uncertainty quantification
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Encoding in style: A stylegan encoder for image-to-image translation
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Stylespace analysis: Disentangled controls for stylegan image generation
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Score-based generative classifiers
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Anastasios N Angelopoulos, Amit P Kohli, Stephen Bates, Michael I Jordan, Jitendra Malik, Thayer Alshaabi, Srigokul Upadhyayula, and Yaniv Romano · 2022
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