Erich Kobler

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Image Reconstruction

Inverse Problems

Diffusion Models

Top Venues

J. Math. Imaging Vis.

Publications

Thomas Pinetz, Erich Kobler, Robert Haase, Julian A. Luetkens, Mathias Meetschen, Johannes Haubold, Cornelius Deuschl, Alexander Radbruch, Katerina Deike, Alexander Effland
Gadolinium dose reduction for brain MRI using conditional deep learning. CoRR (2024)
Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani
A variable metric proximal stochastic gradient method: An application to classification problems. EURO J. Comput. Optim. 12 (2024)
Antonio Ortiz-Gonzalez, Erich Kobler, Stefan Simon, Leon Bischoff, Sebastian Nowak, Alexander Isaak, Wolfgang Block, Alois M. Sprinkart, Ulrike I. Attenberger, Julian A. Luetkens, Eduardo Bayro-Corrochano, Alexander Effland
Optical Flow-Guided Cine MRI Segmentation With Learned Corrections. IEEE Trans. Medical Imaging 43 (3) (2024)
Martin Zach, Erich Kobler, Antonin Chambolle, Thomas Pock
Product of Gaussian Mixture Diffusion Models. J. Math. Imaging Vis. 66 (4) (2024)
Martin Zach, Thomas Pock, Erich Kobler, Antonin Chambolle
Explicit Diffusion of Gaussian Mixture Model Based Image Priors. SSVM (2023)
Thomas Pinetz, Erich Kobler, Robert Haase, Katerina Deike-Hofmann, Alexander Radbruch, Alexander Effland
Faithful Synthesis of Low-Dose Contrast-Enhanced Brain MRI Scans Using Noise-Preserving Conditional GANs. MICCAI (2) (2023)
Thomas Pinetz, Erich Kobler, Robert Haase, Katerina Deike-Hofmann, Alexander Radbruch, Alexander Effland
Faithful Synthesis of Low-dose Contrast-enhanced Brain MRI Scans using Noise-preserving Conditional GANs. CoRR (2023)
Martin Zach, Thomas Pock, Erich Kobler, Antonin Chambolle
Explicit Diffusion of Gaussian Mixture Model Based Image Priors. CoRR (2023)
Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani
Constrained and unconstrained deep image prior optimization models with automatic regularization. Comput. Optim. Appl. 84 (1) (2023)
Erich Kobler, Thomas Pock
Learning Gradually Non-convex Image Priors Using Score Matching. CoRR (2023)
Lydia Lindner, Alexander Effland, Filip Ilic, Thomas Pock, Erich Kobler
Lightweight Video Denoising using Aggregated Shifted Window Attention. WACV (2023)
Ahmed Alshenoudy, Bertram Sabrowsky-Hirsch, Stefan Thumfart, Michael Giretzlehner, Erich Kobler
Semi-supervised Brain Tumor Segmentation Using Diffusion Models. AIAI (1) (2023)
Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock
Total Deep Variation: A Stable Regularization Method for Inverse Problems. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. IEEE Trans. Medical Imaging 41 (2) (2022)
Thomas Pinetz, Erich Kobler, Thomas Pock, Alexander Effland
Blind Single Image Super-Resolution via Iterated Shared Prior Learning. GCPR (2022)
Martin Zach, Erich Kobler, Thomas Pock
Computed Tomography Reconstruction using Generative Energy-Based Priors. CoRR (2022)
Markus Hofinger, Erich Kobler, Alexander Effland, Thomas Pock
Learned Variational Video Color Propagation. ECCV (23) (2022)
Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. CoRR (2021)
Thomas Pinetz, Erich Kobler, Christian Doberstein, Benjamin Berkels, Alexander Effland
Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy. SSVM (2021)
Thomas Pinetz, Erich Kobler, Thomas Pock, Alexander Effland
Shared Prior Learning of Energy-Based Models for Image Reconstruction. SIAM J. Imaging Sci. 14 (4) (2021)
Alexander Effland, Erich Kobler, Thomas Pock, Marko Rajkovic, Martin Rumpf
Image Morphing in Deep Feature Spaces: Theory and Applications. J. Math. Imaging Vis. 63 (2) (2021)
Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock
Total Deep Variation for Linear Inverse Problems. CVPR (2020)
Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock
Total Deep Variation for Linear Inverse Problems. CoRR (2020)
Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock
Total Deep Variation: A Stable Regularizer for Inverse Problems. CoRR (2020)
Alexander Effland, Erich Kobler, Karl Kunisch, Thomas Pock
Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration. J. Math. Imaging Vis. 62 (3) (2020)
Thomas Pinetz, Erich Kobler, Thomas Pock, Alexander Effland
Shared Prior Learning of Energy-Based Models for Image Reconstruction. CoRR (2020)
Elena A. Kaye, Emily A. Aherne, Cihan Duzgol, Ida Häggström, Erich Kobler, Yousef Mazaheri, Maggie M. Fung, Zhigang Zhang, Ricardo Otazo, Herbert Alberto Vargas, Oguz Akin
Accelerating Prostate Diffusion Weighted MRI using Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study. CoRR (2020)
Alexander Effland, Erich Kobler, Thomas Pock, Marko Rajkovic, Martin Rumpf
Image Morphing in Deep Feature Spaces: Theory and Applications. CoRR (2019)
Patricia M. Johnson, Matthew J. Muckley, Mary Bruno, Erich Kobler, Kerstin Hammernik, Thomas Pock, Florian Knoll
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions. MLMIR@MICCAI (2019)
Alexander Effland, Erich Kobler, Karl Kunisch, Thomas Pock
An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration. CoRR (2019)
Alexander Effland, Erich Kobler, Anne Brandenburg, Teresa Klatzer, Leonie Neuhäuser, Michael Hölzel, Jennifer Landsberg, Thomas Pock, Martin Rumpf
Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data. Int. J. Comput. Assist. Radiol. Surg. 14 (4) (2019)
Alexander Effland, Erich Kobler, Thomas Pock, Martin Rumpf
Time Discrete Geodesics in Deep Feature Spaces for Image Morphing. SSVM (2019)
Alexander Effland, Michael Hölzel, Teresa Klatzer, Erich Kobler, Jennifer Landsberg, Leonie Neuhäuser, Thomas Pock, Martin Rumpf
Variational Networks for Joint Image Reconstruction and Classification of Tumor Immune Cell Interactions in Melanoma Tissue Sections. Bildverarbeitung für die Medizin (2018)
Erich Kobler, Matthew J. Muckley, Baiyu Chen, Florian Knoll, Kerstin Hammernik, Thomas Pock, Daniel K. Sodickson, Ricardo Otazo
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP (2018)
Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, Florian Knoll
Learning a Variational Network for Reconstruction of Accelerated MRI Data. CoRR (2017)
Teresa Klatzer, Daniel Soukup, Erich Kobler, Kerstin Hammernik, Thomas Pock
Trainable Regularization for Multi-frame Superresolution. GCPR (2017)
Erich Kobler, Teresa Klatzer, Kerstin Hammernik, Thomas Pock
Variational Networks: Connecting Variational Methods and Deep Learning. GCPR (2017)