Erich Kobler

Orcid: 0000-0001-5167-4804

According to our database1, Erich Kobler authored at least 29 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Optical Flow-Guided Cine MRI Segmentation With Learned Corrections.
IEEE Trans. Medical Imaging, March, 2024

Gadolinium dose reduction for brain MRI using conditional deep learning.
CoRR, 2024

2023
Learning Gradually Non-convex Image Priors Using Score Matching.
CoRR, 2023

Constrained and unconstrained deep image prior optimization models with automatic regularization.
Comput. Optim. Appl., 2023

Lightweight Video Denoising using Aggregated Shifted Window Attention.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Explicit Diffusion of Gaussian Mixture Model Based Image Priors.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Faithful Synthesis of Low-Dose Contrast-Enhanced Brain MRI Scans Using Noise-Preserving Conditional GANs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Semi-supervised Brain Tumor Segmentation Using Diffusion Models.
Proceedings of the Artificial Intelligence Applications and Innovations, 2023

2022
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction.
IEEE Trans. Medical Imaging, 2022

Total Deep Variation: A Stable Regularization Method for Inverse Problems.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Computed Tomography Reconstruction using Generative Energy-Based Priors.
CoRR, 2022

Learned Variational Video Color Propagation.
Proceedings of the Computer Vision - ECCV 2022, 2022

Blind Single Image Super-Resolution via Iterated Shared Prior Learning.
Proceedings of the Pattern Recognition, 2022

2021
Shared Prior Learning of Energy-Based Models for Image Reconstruction.
SIAM J. Imaging Sci., 2021

Image Morphing in Deep Feature Spaces: Theory and Applications.
J. Math. Imaging Vis., 2021

Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

2020
Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration.
J. Math. Imaging Vis., 2020

Accelerating Prostate Diffusion Weighted MRI using Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study.
CoRR, 2020

Total Deep Variation: A Stable Regularizer for Inverse Problems.
CoRR, 2020

Total Deep Variation for Linear Inverse Problems.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration.
CoRR, 2019

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.
Int. J. Comput. Assist. Radiol. Surg., 2019

Time Discrete Geodesics in Deep Feature Spaces for Image Morphing.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019

2018
Variational Deep Learning for Low-Dose Computed Tomography.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Variational Networks for Joint Image Reconstruction and Classification of Tumor Immune Cell Interactions in Melanoma Tissue Sections.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017
Learning a Variational Network for Reconstruction of Accelerated MRI Data.
CoRR, 2017

Variational Networks: Connecting Variational Methods and Deep Learning.
Proceedings of the Pattern Recognition - 39th German Conference, 2017

Trainable Regularization for Multi-frame Superresolution.
Proceedings of the Pattern Recognition - 39th German Conference, 2017


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