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 | 597 | 2018 |
Guided image generation with conditional invertible neural networks L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe arXiv preprint arXiv:1907.02392, 2019 | 310 | 2019 |
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 33 (4), 1452-1466, 2020 | 190 | 2020 |
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 | 102 | 2020 |
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 | 70 | 2020 |
Benchmarking invertible architectures on inverse problems J Kruse, L Ardizzone, C Rother, U Köthe arXiv preprint arXiv:2101.10763, 2021 | 59 | 2021 |
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 | 51 | 2021 |
Conditional invertible neural networks for diverse image-to-image translation L Ardizzone, J Kruse, C Lüth, N Bracher, C Rother, U Köthe Pattern Recognition: 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen ¡¦, 2021 | 44 | 2021 |
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, 997-1007, 2019 | 35 | 2019 |
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 | 25 | 2020 |
Framework for easily invertible architectures (FrEIA) L Ardizzone, T Bungert, F Draxler, U Köthe, J Kruse, R Schmier, ... Source code, 2018 | 24 | 2018 |
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 | 23 | 2021 |
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 | 21 | 2022 |
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 | 16 | 2022 |
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 | 16 | 2018 |
Exoplanet characterization using conditional invertible neural networks J Haldemann, V Ksoll, D Walter, Y Alibert, RS Klessen, W Benz, U Koethe, ... Astronomy & Astrophysics 672, A180, 2023 | 15 | 2023 |
Emission-line diagnostics of H ii regions using conditional invertible neural networks DE Kang, EW Pellegrini, L Ardizzone, RS Klessen, U Koethe, SCO Glover, ... Monthly Notices of the Royal Astronomical Society 512 (1), 617-647, 2022 | 14 | 2022 |
Towards multimodal depth estimation from light fields T Leistner, R Mackowiak, L Ardizzone, U Köthe, C Rother Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ¡¦, 2022 | 13 | 2022 |
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, 1808 | 13 | 1808 |
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 | 10 | 2019 |