Learning a variational network for reconstruction of accelerated MRI data K Hammernik, T Klatzer, E Kobler, MP Recht, DK Sodickson, T Pock, ... Magnetic resonance in medicine 79 (6), 3055-3071, 2018 | 1841 | 2018 |
Variational networks: connecting variational methods and deep learning E Kobler, T Klatzer, K Hammernik, T Pock Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017 | 149 | 2017 |
Learning joint demosaicing and denoising based on sequential energy minimization T Klatzer, K Hammernik, P Knobelreiter, T Pock 2016 IEEE International Conference on Computational Photography (ICCP), 1-11, 2016 | 100 | 2016 |
Continuous Hyper-parameter Learning for Support Vector Machines T Klatzer, T Pock Computer Vision Winter Workshop (CVWW), 2015 | 28 | 2015 |
Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data A Effland, E Kobler, A Brandenburg, T Klatzer, L Neuhäuser, M Hölzel, ... International journal of computer assisted radiology and surgery 14, 587-599, 2019 | 8 | 2019 |
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling T Klatzer, P Dobson, Y Altmann, M Pereyra, JM Sanz-Serna, KC Zygalakis SIAM Journal on Imaging Sciences 17 (2), 1078-1117, 2024 | 4 | 2024 |
Variational networks for joint image reconstruction and classification of tumor immune cell interactions in melanoma tissue sections A Effland, M Hölzel, T Klatzer, E Kobler, J Landsberg, L Neuhäuser, ... Bildverarbeitung für die Medizin 2018: Algorithmen-Systeme-Anwendungen …, 2018 | 3 | 2018 |
Trainable regularization for multi-frame superresolution T Klatzer, D Soukup, E Kobler, K Hammernik, T Pock Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017 | 3 | 2017 |