98 citations · 99 across the 4 of their papers we have counts for
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Unconditional CNN denoisers contain sparse semantic representation of images
Zahra Kadkhodaie, Stéphane Mallat, Eero Simoncelli
Generative diffusion models learn probability densities over diverse image datasets by estimating the score with a neural network trained to remove noise. Despite their remarkable…
Feature-guided score diffusion for sampling conditional densities
Zahra Kadkhodaie, Stéphane Mallat, Eero P. Simoncelli
Score diffusion methods can learn probability densities from samples. The score of the noise-corrupted density is estimated using a deep neural network, which is then used to itera…
Generalization in diffusion models arises from geometry-adaptive harmonic representations
Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli +1
Deep neural networks (DNNs) trained for image denoising are able to generate high-quality samples with score-based reverse diffusion algorithms. These impressive capabilities seem…