Johannes Hertrich
Johannes Hertrich
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Zitiert von
Zitiert von
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
Convolutional proximal neural networks and plug-and-play algorithms
J Hertrich, S Neumayer, G Steidl
Linear Algebra and its Applications 631, 203-234, 2021
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
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
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
Inertial stochastic PALM and applications in machine learning
J Hertrich, G Steidl
Sampling Theory, Signal Processing, and Data Analysis 20 (1), 4, 2022
Wasserstein patch prior for image superresolution
J Hertrich, A Houdard, C Redenbach
IEEE Transactions on Computational Imaging 8, 693-704, 2022
Variational models for color image correction inspired by visual perception and neuroscience
T Batard, J Hertrich, G Steidl
Journal of Mathematical Imaging and Vision 62, 1173-1194, 2020
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization
F Altekrüger, A Denker, P Hagemann, J Hertrich, P Maass, G Steidl
arXiv preprint arXiv:2205.12021, 2022
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution
F Altekrüger, J Hertrich
arXiv preprint arXiv:2201.08157, 2022
Generalized Normalizing Flows via Markov Chains
P Hagemann, J Hertrich, G Steidl
Elements in Non-local Data Interactions: Foundations and Applications, 2023
Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
J Hertrich, M Gräf, R Beinert, G Steidl
arXiv preprint arXiv:2211.01804, 2022
Minimal Lipschitz and∞-harmonic extensions of vector-valued functions on finite graphs
M Bačák, J Hertrich, S Neumayer, G Steidl
Information and Inference: A Journal of the IMA 9 (4), 935-959, 2020
Infinity-Laplacians on scalar-and vector-valued functions and optimal Lipschitz extensions on graphs
J Hertrich
arXiv preprint arXiv:1910.13805, 2019
Sparse Mixture Models inspired by ANOVA Decompositions
J Hertrich, FA Ba, G Steidl
Electronic Transactions on Numerical Analysis 55, 142-168, 2021
Minimal Lipschitz extensions for vector-valued functions on finite graphs
J Hertrich, M Bačák, S Neumayer, G Steidl
Scale Space and Variational Methods in Computer Vision: 7th International …, 2019
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels
F Altekrüger, J Hertrich, G Steidl
arXiv preprint arXiv:2301.11624, 2023
Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
J Hertrich, R Beinert, M Gräf, G Steidl
arXiv preprint arXiv:2301.04441, 2023
Proximal Residual Flows for Bayesian Inverse Problems
J Hertrich
arXiv preprint arXiv:2211.17158, 2022
Image super-resolution with PCA Reduced generalized Gaussian mixture models
DPL Nguyen, J Hertrich, JF Aujol, Y Berthoumieu
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