11 citations · 13 across the 7 of their papers we have counts for
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cs.LG2023★ 2 cited
Elucidating the Exposure Bias in Diffusion Models
Mang Ning, Mingxiao Li, Jianlin Su +2
Diffusion models have demonstrated impressive generative capabilities, but their \textit{exposure bias} problem, described as the input mismatch between training and sampling, lack…
cs.LG2023★ 11 cited
Input Perturbation Reduces Exposure Bias in Diffusion Models
Mang Ning, Enver Sangineto, Angelo Porrello +2
Denoising Diffusion Probabilistic Models have shown an impressive generation quality, although their long sampling chain leads to high computational costs. In this paper, we observ…