| 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 | 780 | 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 | 415 | 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 | 338 | 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 | 140 | 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 | 90 | 2020 |
| Benchmarking invertible architectures on inverse problems J Kruse, L Ardizzone, C Rother, U Köthe arXiv preprint arXiv:2101.10763, 2021 | 72 | 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 | 69 | 2021 |
| 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 | 60 | 2020 |
| Framework for easily invertible architectures (FrEIA) L Ardizzone, T Bungert, F Draxler, U Köthe, J Kruse, R Schmier, ... Source code, 2018 | 43 | 2018 |
| 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 | 42 | 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 | 39 | 2020 |
| 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 | 30 | 2023 |
| 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 | 28 | 2021 |
| 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 | 27 | 2022 |
| 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 | 25 | 2022 |
| Invertible networks or partons to detector and back again, SciPost Phys M Bellagente, A Butter, G Kasieczka, T Plehn, A Rousselot, ... arXiv preprint arXiv:2006.06685, 2020 | 23 | 2020 |
| Framework for Easily Invertible Architectures (FrEIA), 2018-2022 L Ardizzone, T Bungert, F Draxler, U Köthe, J Kruse, R Schmier, ... URL https://github. com/vislearn/FrEIA 755, 0 | 22 | |
| 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 | 20 | 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, 2019 | 20 | 2019 |
| 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 | 18 | 2022 |
