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Loss Curvature as a Sampling-Free Proxy for Memorization in Diffusion Models
Understanding the mechanism behind why diffusion models memorize their training data remains an open question in generative modeling. In this paper, we examine this question from two perspectives: (a) the model-level perspective concerning the onset of memorization in a model during training, and (b
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