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Differentiable Gaussianization Layers for Inverse Problems Regularized
  by Deep Generative Models

Differentiable Gaussianization Layers for Inverse Problems Regularized by Deep Generative Models

7 December 2021
Dongzhuo Li
    MedIm
ArXivPDFHTML

Papers citing "Differentiable Gaussianization Layers for Inverse Problems Regularized by Deep Generative Models"

6 / 6 papers shown
Title
Denoising Diffusion Restoration Models
Denoising Diffusion Restoration Models
Bahjat Kawar
Michael Elad
Stefano Ermon
Jiaming Song
DiffM
204
770
0
27 Jan 2022
Intermediate Layer Optimization for Inverse Problems using Deep
  Generative Models
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras
Joseph Dean
A. Jalal
A. Dimakis
DRL
171
82
0
15 Feb 2021
Preconditioned training of normalizing flows for variational inference
  in inverse problems
Preconditioned training of normalizing flows for variational inference in inverse problems
Ali Siahkoohi
G. Rizzuti
M. Louboutin
Philipp A. Witte
Felix J. Herrmann
56
31
0
11 Jan 2021
Solving Inverse Problems with a Flow-based Noise Model
Solving Inverse Problems with a Flow-based Noise Model
Jay Whang
Qi Lei
A. Dimakis
56
33
0
18 Mar 2020
Stochastic seismic waveform inversion using generative adversarial
  networks as a geological prior
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior
L. Mosser
O. Dubrule
M. Blunt
GAN
AI4CE
66
207
0
10 Jun 2018
Iterative Gaussianization: from ICA to Random Rotations
Iterative Gaussianization: from ICA to Random Rotations
Valero Laparra
Gustavo Camps-Valls
Jesús Malo
51
123
0
31 Jan 2016
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