Web: http://arxiv.org/abs/2205.01490

May 4, 2022, 1:11 a.m. | Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola

cs.LG updates on arXiv.org arxiv.org

Score-based models generate samples by mapping noise to data (and vice versa)
via a high-dimensional diffusion process. We question whether it is necessary
to run this entire process at high dimensionality and incur all the
inconveniences thereof. Instead, we restrict the diffusion via projections onto
subspaces as the data distribution evolves toward noise. When applied to
state-of-the-art models, our framework simultaneously improves sample quality
-- reaching an FID of 2.17 on unconditional CIFAR-10 -- and reduces the
computational cost of …

arxiv models

More from arxiv.org / cs.LG updates on arXiv.org

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California