Johannes Hertrich

50 papers A* 5Journal 40Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DeepInverse: A Python package for solving imaging inverse problems with deep learning. J. Open Source Softw. Julián Tachella, Matthieu Terris, Samuel Hurault, Andrew Wang, Leo Davy, Jérémy Scanvic, Victor Sechaud, Romain Vo, Thomas Moreau, Thomas Davies, Dongdong Chen, Nils Laurent, Brayan Monroy, Jonathan Dong, Zhiyuan Hu, Minh-Hai Nguyen, Florian Sarron, Pierre Weiss, Paul Escande, Mathurin Massias, Thibaut Modrzyk, Brett Levac, Tobías I. Liaudat, Maxime Song, Johannes Hertrich, Sebastian Neumayer, Georg Schramm
2025	A*	`conf`	Fast Summation of Radial Kernels via QMC Slicing. ICLR Johannes Hertrich, Tim Jahn, Michael Quellmalz
2025	J	`jnl`	Generative Feature Training of Thin 2-Layer Networks. Trans. Mach. Learn. Res. Johannes Hertrich, Sebastian Neumayer
2025	A*	`conf`	Importance Corrected Neural JKO Sampling. ICML Johannes Hertrich, Robert Gruhlke
2025	J	`jnl`	Iterative Importance Fine-tuning of Diffusion Models. CoRR Alexander Denker, Shreyas Padhy, Francisco Vargas, Johannes Hertrich
2025	J	`jnl`	Learning Regularization Functionals for Inverse Problems: A Comparative Study. CoRR Johannes Hertrich, Hok Shing Wong, Alexander Denker, Stanislas Ducotterd, Zhenghan Fang, Markus Haltmeier, Zeljko Kereta, Erich Kobler, Oscar Leong, Mohammad Sadegh Salehi, Carola-Bibiane Schönlieb, Johannes Schwab, Zakhar Shumaylov, Jeremias Sulam, German Shâma Wache, Martin Zach, Yasi Zhang, Matthias J. Ehrhardt, Sebastian Neumayer
2025	J	`jnl`	Numerical Methods for Kernel Slicing. CoRR Nicolaj Rux, Johannes Hertrich, Sebastian Neumayer
2025	J	`jnl`	On the Relation between Rectified Flows and Optimal Transport. CoRR Johannes Hertrich, Antonin Chambolle, Julie Delon
2025	—	`conf`	Plug-and-Play Half-Quadratic Splitting for Ptychography. SSVM (1) Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge
2024	J	`jnl`	Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms. CoRR Johannes Hertrich
2024	J	`jnl`	Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms. SIAM J. Math. Data Sci. Johannes Hertrich
2024	J	`jnl`	Fast Summation of Radial Kernels via QMC Slicing. CoRR Johannes Hertrich, Tim Jahn, Michael Quellmalz
2024	J	`jnl`	Generative Feature Training of Thin 2-Layer Networks. CoRR Johannes Hertrich, Sebastian Neumayer
2024	A*	`conf`	Generative Sliced MMD Flows with Riesz Kernels. ICLR Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann
2024	J	`jnl`	Importance Corrected Neural JKO Sampling. CoRR Johannes Hertrich, Robert Gruhlke
2024	J	`jnl`	Manifold Learning by Mixture Models of VAEs for Inverse Problems. J. Mach. Learn. Res. Giovanni S. Alberti, Johannes Hertrich, Matteo Santacesaria, Silvia Sciutto
2024	J	`jnl`	Mixed Noise and Posterior Estimation with Conditional DeepGEM. CoRR Paul Hagemann, Johannes Hertrich, Maren Casfor, Sebastian Heidenreich, Gabriele Steidl
2024	J	`jnl`	Mixed noise and posterior estimation with conditional deepGEM. Mach. Learn. Sci. Technol. Paul Hagemann, Johannes Hertrich, Maren Casfor, Sebastian Heidenreich, Gabriele Steidl
2024	J	`jnl`	Plug-and-Play Half-Quadratic Splitting for Ptychography. CoRR Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge
2024	A*	`conf`	Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel. ICLR Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine, Gabriele Steidl
2023	J	`jnl`	Generative Sliced MMD Flows with Riesz Kernels. CoRR Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann
2023	J	`jnl`	Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction. CoRR Moritz Piening, Fabian Altekrüger, Johannes Hertrich, Paul Hagemann, Andrea Walther, Gabriele Steidl
2023	J	`jnl`	Manifold Learning by Mixture Models of VAEs for Inverse Problems. CoRR Giovanni S. Alberti, Johannes Hertrich, Matteo Santacesaria, Silvia Sciutto
2023	A*	`conf`	Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels. ICML Fabian Altekrüger, Johannes Hertrich, Gabriele Steidl
2023	J	`jnl`	Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels. CoRR Fabian Altekrüger, Johannes Hertrich, Gabriele Steidl
2023	J	`jnl`	Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel. CoRR Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine, Gabriele Steidl
2023	—	`conf`	Proximal Residual Flows for Bayesian Inverse Problems. SSVM Johannes Hertrich
2023	—	`—`	Proximal neural networks and stochastic normalizing flows for inverse problems. Johannes Hertrich
2023	J	`jnl`	WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution. SIAM J. Imaging Sci. Fabian Altekrüger, Johannes Hertrich
2023	—	`conf`	Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line. SSVM Johannes Hertrich, Robert Beinert, Manuel Gräf, Gabriele Steidl
2023	J	`jnl`	Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line. CoRR Johannes Hertrich, Robert Beinert, Manuel Gräf, Gabriele Steidl
2022	J	`jnl`	PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization. CoRR Fabian Altekrüger, Alexander Denker, Paul Hagemann, Johannes Hertrich, Peter Maass, Gabriele Steidl
2022	J	`jnl`	Proximal Residual Flows for Bayesian Inverse Problems. CoRR Johannes Hertrich
2022	J	`jnl`	Stochastic Normalizing Flows for Inverse Problems: A Markov Chains Viewpoint. SIAM/ASA J. Uncertain. Quantification Paul Hagemann, Johannes Hertrich, Gabriele Steidl
2022	J	`jnl`	WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution. CoRR Fabian Altekrüger, Johannes Hertrich
2022	J	`jnl`	Wasserstein Patch Prior for Image Superresolution. IEEE Trans. Computational Imaging Johannes Hertrich, Antoine Houdard, Claudia Redenbach
2022	J	`jnl`	Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels. CoRR Johannes Hertrich, Manuel Gräf, Robert Beinert, Gabriele Steidl
2021	J	`jnl`	A Unified Approach to Variational Autoencoders and Stochastic Normalizing Flows via Markov Chains. CoRR Johannes Hertrich, Paul Hagemann, Gabriele Steidl
2021	J	`jnl`	Alternatives to the EM algorithm for ML estimation of location, scatter matrix, and degree of freedom of the Student t distribution. Numer. Algorithms Marzieh Hasannasab, Johannes Hertrich, Friederike Laus, Gabriele Steidl
2021	J	`jnl`	Correction to: Alternatives to the EM algorithm for ML estimation of location, scatter matrix, and degree of freedom of the Student t distribution. Numer. Algorithms Marzieh Hasannasab, Johannes Hertrich, Friederike Laus, Gabriele Steidl
2021	J	`jnl`	Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint. CoRR Paul Hagemann, Johannes Hertrich, Gabriele Steidl
2021	J	`jnl`	Wasserstein Patch Prior for Image Superresolution. CoRR Johannes Hertrich, Antoine Houdard, Claudia Redenbach
2020	J	`jnl`	Convolutional Proximal Neural Networks and Plug-and-Play Algorithms. CoRR Johannes Hertrich, Sebastian Neumayer, Gabriele Steidl
2020	J	`jnl`	Inertial Stochastic PALM and its Application for Learning Student-t Mixture Models. CoRR Johannes Hertrich, Gabriele Steidl
2020	J	`jnl`	PCA Reduced Gaussian Mixture Models with Applications in Superresolution. CoRR Johannes Hertrich, Dang Phoung Lan Nguyen, Jean-François Aujol, Dominique Bernard, Yannick Berthoumieu, Abdellativ Sa'adaldin, Gabriele Steidl
2020	J	`jnl`	Variational Models for Color Image Correction Inspired by Visual Perception and Neuroscience. J. Math. Imaging Vis. Thomas Batard, Johannes Hertrich, Gabriele Steidl
2019	J	`jnl`	Alternatives of the EM Algorithm for Estimating the Parameters of the Student-t Distribution. CoRR Marzieh Hasannasab, Johannes Hertrich, Friederike Laus, Gabriele Steidl
2019	J	`jnl`	Infinity-Laplacians on Scalar- and Vector-Valued Functions and Optimal Lipschitz Extensions on Graphs. CoRR Johannes Hertrich
2019	—	`conf`	Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphs. SSVM Johannes Hertrich, Miroslav Bacák, Sebastian Neumayer, Gabriele Steidl
2019	J	`jnl`	Parseval Proximal Neural Networks. CoRR Marzieh Hasannasab, Johannes Hertrich, Sebastian Neumayer, Gerlind Plonka, Simon Setzer, Gabriele Steidl