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Johannes Hertrich
Johannes Hertrich
Université Paris-Dauphine
Verifisert e-postadresse på dauphine.psl.eu - Startside
Tittel
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Sitert av
År
Convolutional proximal neural networks and plug-and-play algorithms
J Hertrich, S Neumayer, G Steidl
Linear Algebra and its Applications 631, 203-234, 2021
612021
Parseval proximal neural networks
M Hasannasab, J Hertrich, S Neumayer, G Plonka, S Setzer, G Steidl
Journal of Fourier Analysis and Applications 26, 1-31, 2020
602020
Stochastic normalizing flows for inverse problems: A Markov chains viewpoint
P Hagemann, J Hertrich, G Steidl
SIAM/ASA Journal on Uncertainty Quantification 10 (3), 1162-1190, 2022
532022
PatchNR: learning from very few images by patch normalizing flow regularization
F Altekrüger, A Denker, P Hagemann, J Hertrich, P Maass, G Steidl
Inverse Problems 39 (6), 064006, 2023
36*2023
Generalized Normalizing Flows via Markov Chains
P Hagemann, J Hertrich, G Steidl
Elements in Non-local Data Interactions: Foundations and Applications, 2023
302023
PCA reduced Gaussian mixture models with applications in superresolution
J Hertrich, DPL Nguyen, JF Aujol, D Bernard, Y Berthoumieu, A Saadaldin, ...
Inverse Problems and Imaging 16 (2), 341-366, 2022
272022
Posterior sampling based on gradient flows of the MMD with negative distance kernel
P Hagemann, J Hertrich, F Altekrüger, R Beinert, J Chemseddine, G Steidl
International Conference on Learning Representations (ICLR) 2024, 2024
242024
Wasserstein patch prior for image superresolution
J Hertrich, A Houdard, C Redenbach
IEEE Transactions on Computational Imaging 8, 693-704, 2022
232022
Alternatives to the EM algorithm for ML estimation of location, scatter matrix, and degree of freedom of the student t distribution
M Hasannasab, J Hertrich, F Laus, G Steidl
Numerical Algorithms 87 (1), 77-118, 2021
232021
Inertial stochastic PALM and applications in machine learning
J Hertrich, G Steidl
Sampling Theory, Signal Processing, and Data Analysis 20, 1-33, 2022
21*2022
Wasserstein steepest descent flows of discrepancies with Riesz kernels
J Hertrich, M Gräf, R Beinert, G Steidl
Journal of Mathematical Analysis and Applications 531 (1), 127829, 2024
202024
Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels
F Altekrüger, J Hertrich, G Steidl
International Conference on Machine Learning (ICML) 2023, 2023
20*2023
Generative sliced MMD flows with Riesz kernels
J Hertrich, C Wald, F Altekrüger, P Hagemann
International Conference on Learning Representations (ICLR) 2024, 2024
192024
WPPNets and WPPFlows: The power of Wasserstein patch priors for superresolution
F Altekrüger, J Hertrich
SIAM Journal on Imaging Sciences 16 (3), 1033-1067, 2023
182023
Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
J Hertrich, R Beinert, M Gräf, G Steidl
International Conference on Scale Space and Variational Methods in Computer …, 2023
102023
Manifold learning by mixture models of VAEs for inverse problems
GS Alberti, J Hertrich, M Santacesaria, S Sciutto
Journal of Machine Learning Research 25 (202), 1-35, 2024
92024
Proximal residual flows for Bayesian inverse problems
J Hertrich
International Conference on Scale Space and Variational Methods in Computer …, 2023
52023
Fast kernel summation in high dimensions via slicing and Fourier transforms
J Hertrich
SIAM Journal on Mathematics of Data Science 6 (4), 1109-1137, 2024
42024
Learning from small data sets: Patch‐based regularizers in inverse problems for image reconstruction
M Piening, F Altekrüger, J Hertrich, P Hagemann, A Walther, G Steidl
GAMM‐Mitteilungen 47 (4), e202470002, 2024
42024
Importance corrected neural JKO sampling
J Hertrich, R Gruhlke
arXiv preprint arXiv:2407.20444, 2024
42024
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Artikler 1–20