Jonas Adler
Jonas Adler
Senior Research Scientist, Google DeepMind
Geverifieerd e-mailadres voor google.com - Homepage
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Solving ill-posed inverse problems using iterative deep neural networks
J Adler, O Öktem
Inverse Problems 33 (12), 124007, 2017
2402017
Learned primal-dual reconstruction
J Adler, O Öktem
IEEE transactions on medical imaging, 2018
2352018
Model-based learning for accelerated, limited-view 3-d photoacoustic tomography
A Hauptmann, F Lucka, M Betcke, N Huynh, J Adler, B Cox, P Beard, ...
IEEE transactions on medical imaging 37 (6), 1382-1393, 2018
1092018
Banach Wasserstein GAN
J Adler, S Lunz
Neural Information Processing Systems, 2018
582018
Operator discretization library (ODL)
J Adler, H Kohr, O Öktem
Software available from https://github. com/odlgroup/odl, 2017
43*2017
Deep bayesian inversion
J Adler, O Öktem
arXiv preprint arXiv:1811.05910, 2018
302018
Learning to solve inverse problems using Wasserstein loss
J Adler, A Ringh, O Öktem, J Karlsson
arXiv preprint arXiv:1710.10898, 2017
182017
Task adapted reconstruction for inverse problems
J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem
arXiv preprint arXiv:1809.00948, 2018
92018
Data-driven nonsmooth optimization
S Banert, A Ringh, J Adler, J Karlsson, O Oktem
SIAM Journal on Optimization 30 (1), 102-131, 2020
82020
Multi-scale learned iterative reconstruction
A Hauptmann, J Adler, SR Arridge, O Oktem
IEEE Transactions on Computational Imaging, 2020
52020
Deep learning framework for digital breast tomosynthesis reconstruction
N Moriakov, K Michielsen, J Adler, R Mann, I Sechopoulos, J Teuwen
Medical Imaging 2019: Physics of Medical Imaging 10948, 1094804, 2019
52019
EDS tomographic reconstruction regularized by total nuclear variation joined with HAADF-STEM tomography
Z Zhong, WJ Palenstijn, J Adler, KJ Batenburg
Ultramicroscopy 191, 34-43, 2018
52018
On the unreasonable effectiveness of CNNs
A Hauptmann, J Adler
arXiv preprint arXiv:2007.14745, 2020
22020
A unified representation network for segmentation with missing modalities
K Lau, J Adler, J Sjölund
arXiv preprint arXiv:1908.06683, 2019
22019
Deep posterior sampling: Uncertainty quantification for large scale inverse problems
J Adler, O Öktem
International Conference on Medical Imaging with Deep Learning--Extended …, 2019
22019
A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images
A Ashfaq, J Adler
CMBEBIH 2017, 531-538, 2017
12017
GPU Monte Carlo scatter calculations for Cone Beam Computed Tomography
J Adler
12014
Posterior image sampling using statistical learning model
JA Adler, O Öktem
US Patent App. 15/929,940, 2020
2020
Generation of realizable radiotherapy plans
JO Sjölund, JA Adler
US Patent App. 16/352,260, 2020
2020
Computing radiotherapy dose distribution
M Eriksson, JO Sjölund, L Öström, DA Tilly, P Kimstrand, JA Adler
US Patent App. 16/563,139, 2020
2020
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Artikelen 1–20