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Diffusion Posterior Sampling is Computationally Intractable
Diffusion models are a remarkably effective way of learning and sampling from a distribution $p(x)$.
Sample-Efficient Training for Diffusion
Score-based diffusion models have become the most popular approach to deep generative modeling of images, largely due to their empirical performance and reliability.
L1 Regression with Lewis Weights Subsampling
We consider the problem of finding an approximate solution to $\ell_1$ regression while only observing a small number of labels.
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