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Johannes Schwab
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NETT: Solving inverse problems with deep neural networks
H Li, J Schwab, S Antholzer, M Haltmeier
Inverse Problems 36 (6), 065005, 2020
3212020
Deep learning for photoacoustic tomography from sparse data
S Antholzer, M Haltmeier, J Schwab
Inverse problems in science and engineering 27 (7), 987-1005, 2019
3172019
Deep null space learning for inverse problems: convergence analysis and rates
J Schwab, S Antholzer, M Haltmeier
Inverse Problems 35 (2), 025008, 2019
1332019
Photoacoustic image reconstruction via deep learning
S Antholzer, M Haltmeier, R Nuster, J Schwab
Photons plus ultrasound: Imaging and sensing 2018 10494, 433-442, 2018
702018
Real-time photoacoustic projection imaging using deep learning
J Schwab, S Antholzer, R Nuster, M Haltmeier
arXiv preprint arXiv:1801.06693, 2018
55*2018
NETT regularization for compressed sensing photoacoustic tomography
S Antholzer, J Schwab, J Bauer-Marschallinger, P Burgholzer, ...
Photons plus ultrasound: imaging and sensing 2019 10878, 272-282, 2019
462019
DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images
J Schwab, D Kimanius, A Burt, T Dendooven, SHW Scheres
Nature Methods 21 (10), 1855-1862, 2024
272024
Cryo-EM structure of the complete inner kinetochore of the budding yeast point centromere
T Dendooven, Z Zhang, J Yang, SH McLaughlin, J Schwab, SHW Scheres, ...
Science advances 9 (30), eadg7480, 2023
272023
Deep synthesis network for regularizing inverse problems
D Obmann, J Schwab, M Haltmeier
Inverse Problems 37 (1), 015005, 2020
27*2020
Deep learning of truncated singular values for limited view photoacoustic tomography
J Schwab, S Antholzer, R Nuster, G Paltauf, M Haltmeier
Photons Plus Ultrasound: Imaging and Sensing 2019 10878, 254-262, 2019
272019
Learned backprojection for sparse and limited view photoacoustic tomography
J Schwab, S Antholzer, M Haltmeier
Photons Plus Ultrasound: Imaging and Sensing 2019 10878, 263-271, 2019
262019
Regularization of inverse problems by filtered diagonal frame decomposition
A Ebner, J Frikel, D Lorenz, J Schwab, M Haltmeier
Applied and Computational Harmonic Analysis 62, 66-83, 2023
232023
Big in Japan: Regularizing networks for solving inverse problems
J Schwab, S Antholzer, M Haltmeier
Journal of mathematical imaging and vision 62 (3), 445-455, 2020
232020
Deep Learning Versus -Minimization for Compressed Sensing Photoacoustic Tomography
S Antholzer, J Schwab, M Haltmeier
2018 IEEE International Ultrasonics Symposium (IUS), 206-212, 2018
232018
Augmented NETT regularization of inverse problems
D Obmann, L Nguyen, J Schwab, M Haltmeier
Journal of Physics Communications 5 (10), 105002, 2021
212021
A Galerkin least squares approach for photoacoustic tomography
J Schwab, S Pereverzyev Jr, M Haltmeier
SIAM Journal on Numerical Analysis 56 (1), 160-184, 2018
172018
Sparse anett for solving inverse problems with deep learning
D Obmann, L Nguyen, J Schwab, M Haltmeier
2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI …, 2020
12*2020
Sparse synthesis regularization with deep neural networks
D Obmann, J Schwab, M Haltmeier
2019 13th International conference on Sampling Theory and Applications …, 2019
72019
Data-consistent neural networks for solving nonlinear inverse problems
YE Boink, M Haltmeier, S Holman, J Schwab
Inverse Problems and Imaging 17 (1), 203-229, 2023
62023
Confronting heterogeneity in cryogenic electron microscopy data: Innovative strategies and future perspectives with data-driven methods
D Kimanius, J Schwab
Current Opinion in Structural Biology 86, 102815, 2024
22024
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Artikler 1–20