4 papers
Multi-layer State Evolution Under Random Convolutional Design
Mara Daniels, Cédric Gerbelot, Cédric Gerbelot +3
Signal recovery under generative neural network priors has emerged as a promising direction in statistical inference and computational imaging. Theoretical analysis of reconstructi…
On the Contractivity of Stochastic Interpolation Flow
Mara Daniels
We investigate stochastic interpolation, a recently introduced framework for high dimensional sampling which bears many similarities to diffusion modeling. Stochastic interpolation…
Score-based Generative Neural Networks for Large-Scale Optimal Transport
Mara Daniels, Tyler Maunu, Paul Hand
We consider the fundamental problem of sampling the optimal transport coupling between given source and target distributions. In certain cases, the optimal transport plan takes the…
Reducing the Representation Error of GAN Image Priors Using the Deep Decoder
Mara Daniels, Paul Hand, Reinhard Heckel
Generative models, such as GANs, learn an explicit low-dimensional representation of a particular class of images, and so they may be used as natural image priors for solving inver…