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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.
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