127 citations · 461 across the 16 of their papers we have counts for
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cs.LG2023★ 3 cited
Denoising Diffusion Samplers
Francisco Vargas, Will Grathwohl, Arnaud Doucet
Denoising diffusion models are a popular class of generative models providing state-of-the-art results in many domains. One adds gradually noise to data using a diffusion to transf…
cs.LG2023★ 15 cited
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
Yilun Du, Conor Durkan, Robin Strudel +6
Since their introduction, diffusion models have quickly become the prevailing approach to generative modeling in many domains. They can be interpreted as learning the gradients of…