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2009.02994
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Stabilizing Invertible Neural Networks Using Mixture Models
Inverse Problems (IP), 2020
7 September 2020
Paul Hagemann
Sebastian Neumayer
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Papers citing
"Stabilizing Invertible Neural Networks Using Mixture Models"
27 / 27 papers shown
Adapting Noise to Data: Generative Flows from 1D Processes
Jannis Chemseddine
Gregor Kornhardt
Richard Duong
Gabriele Steidl
DiffM
AI4CE
246
0
0
14 Oct 2025
Slicing the Gaussian Mixture Wasserstein Distance
Moritz Piening
Robert Beinert
250
3
0
11 Apr 2025
(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition Number
Rossen Nenov
Daniel Haider
Péter Balázs
103
4
0
30 Sep 2024
Stable Training of Normalizing Flows for High-dimensional Variational Inference
Daniel Andrade
BDL
TPM
218
5
0
26 Feb 2024
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview
Alexander Auras
Kanchana Vaishnavi Gandikota
Hannah Droege
Michael Moeller
AAML
263
1
0
19 Feb 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction
Moritz Piening
Fabian Altekrüger
J. Hertrich
Paul Hagemann
Andrea Walther
Gabriele Steidl
253
8
0
27 Dec 2023
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning
Conference on Robot Learning (CoRL), 2023
Jianxiang Feng
Jongseok Lee
Simon Geisler
Stephan Gunnemann
Rudolph Triebel
OODD
235
7
0
11 Nov 2023
Convergence and Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems
Journal of Mathematical Imaging and Vision (JMIV), 2023
Nathan Buskulic
M. Fadili
Yvain Quéau
413
7
0
21 Sep 2023
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks
Neural Networks (Neural Netw.), 2023
Bangti Jin
Zehui Zhou
Jun Zou
271
4
0
18 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling
Ullrich Kothe
227
11
0
04 Aug 2023
Normalizing flow sampling with Langevin dynamics in the latent space
Machine-mediated learning (ML), 2023
Florentin Coeurdoux
N. Dobigeon
P. Chainais
DRL
149
9
0
20 May 2023
Piecewise Normalizing Flows
H. Bevins
Will Handley
Thomas Gessey-Jones
220
1
0
04 May 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
SIAM Journal of Imaging Sciences (JSIS), 2023
Ziruo Cai
Junqi Tang
Subhadip Mukherjee
Jinglai Li
Carola Bibiane Schönlieb
Xiaoqun Zhang
AI4CE
228
8
0
17 Apr 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
Fabian Altekrüger
Paul Hagemann
Gabriele Steidl
TPM
305
10
0
28 Mar 2023
Proximal Residual Flows for Bayesian Inverse Problems
Scale Space and Variational Methods in Computer Vision (SSVM), 2022
J. Hertrich
BDL
TPM
225
4
0
30 Nov 2022
A Neural-Network-Based Convex Regularizer for Inverse Problems
IEEE Transactions on Computational Imaging (TCI), 2022
Alexis Goujon
Sebastian Neumayer
Pakshal Bohra
Stanislas Ducotterd
M. Unser
375
41
0
22 Nov 2022
Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions
Journal of machine learning research (JMLR), 2022
Stanislas Ducotterd
Alexis Goujon
Pakshal Bohra
Dimitris Perdios
Sebastian Neumayer
M. Unser
247
19
0
28 Oct 2022
Can Push-forward Generative Models Fit Multimodal Distributions?
Neural Information Processing Systems (NeurIPS), 2022
Antoine Salmona
Valentin De Bortoli
J. Delon
A. Desolneux
DiffM
275
45
0
29 Jun 2022
Stability of Image-Reconstruction Algorithms
IEEE Transactions on Computational Imaging (TCI), 2022
Pol del Aguila Pla
Sebastian Neumayer
M. Unser
356
11
0
14 Jun 2022
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization
Inverse Problems (IP), 2022
Fabian Altekrüger
Alexander Denker
Paul Hagemann
J. Hertrich
Peter Maass
Gabriele Steidl
MedIm
296
30
0
24 May 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Sebastian Neumayer
Alexis Goujon
Pakshal Bohra
M. Unser
148
17
0
13 Apr 2022
Generalized Normalizing Flows via Markov Chains
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDL
DiffM
AI4CE
435
27
0
24 Nov 2021
Resampling Base Distributions of Normalizing Flows
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Vincent Stimper
Bernhard Schölkopf
José Miguel Hernández-Lobato
BDL
209
41
0
29 Oct 2021
Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDL
480
45
0
23 Sep 2021
An Introduction to Deep Generative Modeling
GAMM-Mitteilungen (GAMM-Mitteilungen), 2021
Lars Ruthotto
E. Haber
AI4CE
342
277
0
09 Mar 2021
Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence
Scale Space and Variational Methods in Computer Vision (SSVM), 2021
A. Andrle
N. Farchmin
Paul Hagemann
Sebastian Heidenreich
V. Soltwisch
Gabriele Steidl
245
18
0
05 Feb 2021
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms
J. Hertrich
Sebastian Neumayer
Gabriele Steidl
235
70
0
04 Nov 2020
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