750 citations · 1.4k across the 5 of their papers we have counts for
4 papers · 1 filter
Multistep Distillation of Diffusion Models via Moment Matching
Tim Salimans, Thomas Mensink, Jonathan Heek +1
We present a new method for making diffusion models faster to sample. The method distills many-step diffusion models into few-step models by matching conditional expectations of th…
Classifier-Free Diffusion Guidance
Jonathan Ho, Tim Salimans
Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as low temperat…
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Tim Salimans, Andrej Karpathy, Xi Chen +1
PixelCNNs are a recently proposed class of powerful generative models with tractable likelihood. Here we discuss our implementation of PixelCNNs which we make available at https://…
Variational Lossy Autoencoder
Xi Chen, Diederik P. Kingma, Tim Salimans +5
Representation learning seeks to expose certain aspects of observed data in a learned representation that's amenable to downstream tasks like classification. For instance, a good r…