10 citations · 25 across the 7 of their papers we have counts for
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cs.DS2023★ 3 cited
Learning Mixtures of Gaussians Using the DDPM Objective
Kulin Shah, Sitan Chen, Adam Klivans
Recent works have shown that diffusion models can learn essentially any distribution provided one can perform score estimation. Yet it remains poorly understood under what settings…
cs.LG2023★ 10 cited
Ambient Diffusion: Learning Clean Distributions from Corrupted Data
Giannis Daras, Kulin Shah, Yuval Dagan +3
We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples. This problem arises in scientific applications where acce…