| 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 | 630 | 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 | 334 | 2019 |
| Learning to push the limits of efficient FFT-based image deconvolution J Kruse, C Rother, U Schmidt Proceedings of the IEEE International Conference on Computer Vision, 4586-4594, 2017 | 112 | 2017 |
| Benchmarking invertible architectures on inverse problems J Kruse, L Ardizzone, C Rother, U Köthe arXiv preprint arXiv:2101.10763, 2021 | 60 | 2021 |
| HINT: Hierarchical invertible neural transport for density estimation and Bayesian inference J Kruse, G Detommaso, U Köthe, R Scheichl Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8191-8199, 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 | 46 | 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, 1-11, 2019 | 38 | 2019 |
| Framework for easily invertible architectures (FrEIA) L Ardizzone, T Bungert, F Draxler, U Köthe, J Kruse, R Schmier, ... Source code, 2018 | 26 | 2018 |
| Technical report: Training mixture density networks with full covariance matrices J Kruse arXiv preprint arXiv:2003.05739, 2020 | 13 | 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, 0 | 12 | |
| Towards learned emulation of interannual water isotopologue variations in General Circulation Models J Wider, J Kruse, N Weitzel, JC Bühler, U Köthe, K Rehfeld Environmental Data Science 2, e35, 2023 | | 2023 |
| Conditional normalizing flow for predicting the occurrence of rare extreme events on long time scales J Kruse, B Ellerhoff, U Köthe, K Rehfeld EGU General Assembly Conference Abstracts, EGU22-8656, 2022 | | 2022 |
Lynton ArdizzoneHeidelberg University在 iwr.uni-heidelberg.de 的電子郵件地址已通過驗證
