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A Bayesian Perspective on the Deep Image Prior

A Bayesian Perspective on the Deep Image Prior

16 April 2019
Zezhou Cheng
Matheus Gadelha
Subhransu Maji
Daniel Sheldon
    BDL
    UQCV
ArXivPDFHTML

Papers citing "A Bayesian Perspective on the Deep Image Prior"

25 / 25 papers shown
Title
DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration
DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration
Suraj Singh
Anastasia Batsheva
Oleg Y. Rogov
Ahmed Bouridane
46
0
0
20 Mar 2025
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Hongwei Tan
Ziruo Cai
Marcelo Pereyra
Subhadip Mukherjee
Junqi Tang
Carola-Bibiane Schönlieb
SSL
76
1
0
08 Apr 2024
On normalization-equivariance properties of supervised and unsupervised
  denoising methods: a survey
On normalization-equivariance properties of supervised and unsupervised denoising methods: a survey
Sébastien Herbreteau
Charles Kervrann
OOD
48
0
0
23 Feb 2024
Deep Internal Learning: Deep Learning from a Single Input
Deep Internal Learning: Deep Learning from a Single Input
Tom Tirer
Raja Giryes
Se Young Chun
Yonina C. Eldar
36
3
0
12 Dec 2023
Cross-modal Cognitive Consensus guided Audio-Visual Segmentation
Cross-modal Cognitive Consensus guided Audio-Visual Segmentation
Zhaofeng Shi
Qingbo Wu
Fanman Meng
Linfeng Xu
Hongliang Li
VOS
33
3
0
10 Oct 2023
One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from
  Electromagnetic Solvers
One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from Electromagnetic Solvers
Sriram Ravula
Varun Gorti
Bo Deng
Swagato Chakraborty
J. Pingenot
B. Mutnury
D. Wallace
D. Winterberg
Adam R. Klivans
A. Dimakis
30
1
0
06 Jun 2023
Discovering Structure From Corruption for Unsupervised Image
  Reconstruction
Discovering Structure From Corruption for Unsupervised Image Reconstruction
Oscar Leong
Angela F. Gao
He Sun
Katherine Bouman
44
5
0
12 Apr 2023
Uncertainty Estimation for Computed Tomography with a Linearised Deep
  Image Prior
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior
Javier Antorán
Riccardo Barbano
Johannes Leuschner
José Miguel Hernández-Lobato
Bangti Jin
UQCV
45
10
0
28 Feb 2022
Posterior temperature optimized Bayesian models for inverse problems in
  medical imaging
Posterior temperature optimized Bayesian models for inverse problems in medical imaging
M. Laves
Malte Tolle
Alexander Schlaefer
Sandy Engelhardt
45
10
0
02 Feb 2022
Early Stopping for Deep Image Prior
Early Stopping for Deep Image Prior
Hengkang Wang
Taihui Li
Zhong Zhuang
Tiancong Chen
Hengyue Liang
Ju Sun
31
63
0
11 Dec 2021
An Educated Warm Start For Deep Image Prior-Based Micro CT
  Reconstruction
An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction
Riccardo Barbano
Johannes Leuschner
Maximilian Schmidt
Alexander Denker
A. Hauptmann
Peter Maass
Bangti Jin
48
19
0
23 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent
  Advances and Applications
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications
Xinlei Zhou
Han Liu
Farhad Pourpanah
T. Zeng
Xizhao Wang
UQCV
UD
29
58
0
03 Nov 2021
Unsupervised PET Reconstruction from a Bayesian Perspective
Unsupervised PET Reconstruction from a Bayesian Perspective
Chenyu Shen
Wenjun Xia
H. Ye
Mingzheng Hou
Hu Chen
Yan Liu
Jiliu Zhou
Yi Zhang
36
3
0
29 Oct 2021
Deep Bayesian inference for seismic imaging with tasks
Deep Bayesian inference for seismic imaging with tasks
Ali Siahkoohi
G. Rizzuti
Felix J. Herrmann
BDL
UQCV
40
21
0
10 Oct 2021
NPBDREG: Uncertainty Assessment in Diffeomorphic Brain MRI Registration
  using a Non-parametric Bayesian Deep-Learning Based Approach
NPBDREG: Uncertainty Assessment in Diffeomorphic Brain MRI Registration using a Non-parametric Bayesian Deep-Learning Based Approach
Samah Khawaled
Moti Freiman
UQCV
39
8
0
15 Aug 2021
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite
  Width Neural Networks
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks
Adityanarayanan Radhakrishnan
George Stefanakis
M. Belkin
Caroline Uhler
35
25
0
31 Jul 2021
On Measuring and Controlling the Spectral Bias of the Deep Image Prior
On Measuring and Controlling the Spectral Bias of the Deep Image Prior
Prithvijit Chakrabarty
Pascal Mettes
Subhransu Maji
Cees G. M. Snoek
13
60
0
02 Jul 2021
Posterior Sampling for Image Restoration using Explicit Patch Priors
Posterior Sampling for Image Restoration using Explicit Patch Priors
Roy Friedman
Yair Weiss
45
5
0
20 Apr 2021
Unsupervised Shape Completion via Deep Prior in the Neural Tangent
  Kernel Perspective
Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective
Lei Chu
Hao Pan
Wenping Wang
3DPC
34
11
0
19 Apr 2021
Uncertainty quantification in imaging and automatic horizon tracking: a
  Bayesian deep-prior based approach
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach
Ali Siahkoohi
G. Rizzuti
Felix J. Herrmann
25
20
0
01 Apr 2020
Computed Tomography Reconstruction Using Deep Image Prior and Learned
  Reconstruction Methods
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods
Daniel Otero Baguer
Johannes Leuschner
Maximilian Schmidt
29
186
0
10 Mar 2020
Inferring 3D Shapes from Image Collections using Adversarial Networks
Inferring 3D Shapes from Image Collections using Adversarial Networks
Matheus Gadelha
Aartika Rai
Subhransu Maji
Rui Wang
GAN
12
6
0
11 Jun 2019
DeepRED: Deep Image Prior Powered by RED
DeepRED: Deep Image Prior Powered by RED
G. Mataev
Michael Elad
P. Milanfar
SupR
28
191
0
25 Mar 2019
Regularization by architecture: A deep prior approach for inverse
  problems
Regularization by architecture: A deep prior approach for inverse problems
Sören Dittmer
T. Kluth
Peter Maass
Daniel Otero Baguer
35
97
0
10 Dec 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
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