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Lynton Ardizzone
Lynton Ardizzone
Verified email at iwr.uni-heidelberg.de - Homepage
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Cited by
Cited by
Year
Analyzing inverse problems with invertible neural networks
L Ardizzone, J Kruse, S Wirkert, D Rahner, EW Pellegrini, RS Klessen, ...
arXiv preprint arXiv:1808.04730, 2018
2582018
Guided image generation with conditional invertible neural networks
L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe
arXiv preprint arXiv:1907.02392, 2019
1142019
BayesFlow: Learning complex stochastic models with invertible neural networks
ST Radev, UK Mertens, A Voss, L Ardizzone, U Köthe
IEEE transactions on neural networks and learning systems, 2020
412020
Invertible networks or partons to detector and back again
M Bellagente, A Butter, G Kasieczka, T Plehn, A Rousselot, ...
SciPost Physics 9 (5), 074, 2020
312020
Training normalizing flows with the information bottleneck for competitive generative classification
L Ardizzone, R Mackowiak, C Rother, U Köthe
Advances in Neural Information Processing Systems 33, 7828-7840, 2020
242020
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
TJ Adler, L Ardizzone, A Vemuri, L Ayala, J Gröhl, T Kirchner, S Wirkert, ...
International journal of computer assisted radiology and surgery 14 (6), 997 …, 2019
192019
Generative classifiers as a basis for trustworthy image classification
R Mackowiak, L Ardizzone, U Kothe, C Rother
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
182021
Benchmarking invertible architectures on inverse problems
J Kruse, L Ardizzone, C Rother, U Köthe
arXiv preprint arXiv:2101.10763, 2021
172021
Stellar parameter determination from photometry using invertible neural networks
VF Ksoll, L Ardizzone, R Klessen, U Koethe, E Sabbi, M Robberto, ...
Monthly Notices of the Royal Astronomical Society 499 (4), 5447-5485, 2020
102020
Learning robust models using the principle of independent causal mechanisms
J Müller, R Schmier, L Ardizzone, C Rother, U Köthe
DAGM German Conference on Pattern Recognition, 79-110, 2021
82021
Hint: Hierarchical invertible neural transport for general and sequential bayesian inference
G Detommaso, J Kruse, L Ardizzone, C Rother, U Köthe, R Scheichl
stat 1050, 25, 2019
72019
Conditional invertible neural networks for diverse image-to-image translation
L Ardizzone, J Kruse, C Lüth, N Bracher, C Rother, U Köthe
DAGM German Conference on Pattern Recognition, 373-387, 2020
62020
Guided Image Generation with Conditional Invertible Neural Networks.(2019)
L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe
arXiv preprint arXiv:1907.02392, 2018
62018
Analyzing inverse problems with invertible neural networks,(2018)
L Ardizzone, J Kruse, S Wirkert, D Rahner, EW Pellegrini, RS Klessen, ...
arXiv preprint arXiv:1808.04730, 0
6
Invertible neural networks for uncertainty quantification in photoacoustic imaging
JH Nölke, T Adler, J Gröhl, T Kirchner, L Ardizzone, C Rother, U Köthe, ...
Bildverarbeitung für die Medizin 2021, 330-335, 2021
42021
Out of distribution detection for intra-operative functional imaging
TJ Adler, L Ayala, L Ardizzone, HG Kenngott, A Vemuri, BP Müller-Stich, ...
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and …, 2019
32019
Model updating of wind turbine blade cross sections with invertible neural networks
P Noever‐Castelos, L Ardizzone, C Balzani
Wind Energy 25 (3), 573-599, 2022
22022
Representing ambiguity in registration problems with conditional invertible neural networks
D Trofimova, T Adler, L Kausch, L Ardizzone, K Maier-Hein, U Köthe, ...
arXiv preprint arXiv:2012.08195, 2020
22020
Review of Disentanglement Approaches for Medical Applications--Towards Solving the Gordian Knot of Generative Models in Healthcare
J Fragemann, L Ardizzone, J Egger, J Kleesiek
arXiv preprint arXiv:2203.11132, 2022
12022
Training invertible neural networks as autoencoders
L Ardizzone, U Köthe
German Conference on Pattern Recognition, 442-455, 2019
12019
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