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cs.LG2022★ 15 cited
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen, Sinho Chewi, Jerry Li +3
We provide theoretical convergence guarantees for score-based generative models (SGMs) such as denoising diffusion probabilistic models (DDPMs), which constitute the backbone of la…
cs.LG2022
Learning Polynomial Transformations
Sitan Chen, Jerry Li, Yuanzhi Li +1
We consider the problem of learning high dimensional polynomial transformations of Gaussians. Given samples of the form , where is hidden and $p:…