74 citations · 231 across the 27 of their papers we have counts for
5 papers · 1 filter
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
Litu Rout, Negin Raoof, Giannis Daras +3
We present the first framework to solve linear inverse problems leveraging pre-trained latent diffusion models. Previously proposed algorithms (such as DPS and DDRM) only apply to…
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…
DataComp: In search of the next generation of multimodal datasets
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang +31
Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model arch…
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplers
Sitan Chen, Giannis Daras, Alexandros G. Dimakis
We develop a framework for non-asymptotic analysis of deterministic samplers used for diffusion generative modeling. Several recent works have analyzed stochastic samplers using to…
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent
Giannis Daras, Yuval Dagan, Alexandros G. Dimakis +1
Imperfect score-matching leads to a shift between the training and the sampling distribution of diffusion models. Due to the recursive nature of the generation process, errors in p…