20 citations · 32 across the 18 of their papers we have counts for
4 papers · 1 filter
On the spectral properties of generative denoiser Jacobians
Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras
Generative denoising models, such as diffusion and flow-matching, learn to sample from complex distributions by training a deep neural network denoiser to recover clean data from n…
GFlowNet-EM for learning compositional latent variable models
Edward J. Hu, Nikolay Malkin, Moksh Jain +3
Latent variable models (LVMs) with discrete compositional latents are an important but challenging setting due to a combinatorially large number of possible configurations of the l…
Diffusion models as plug-and-play priors
Alexandros Graikos, Esmeralda S. Whitammer, Nebojsa Jojic +1
We consider the problem of inferring high-dimensional data in a model that consists of a prior and an auxiliary differentiable constraint $c(\mathbf{x}…
Resolving label uncertainty with implicit posterior models
Esther Rolf, Nikolay Malkin, Alexandros Graikos +3
We propose a method for jointly inferring labels across a collection of data samples, where each sample consists of an observation and a prior belief about the label. By implicitly…