| Stochastic normalizing flows for inverse problems: a Markov Chains viewpoint P Hagemann, J Hertrich, G Steidl SIAM/ASA Journal on Uncertainty Quantification 10 (3), 1162-1190, 2022 | 41 | 2022 |
| Stabilizing invertible neural networks using mixture models P Hagemann, S Neumayer Inverse Problems 37 (8), 085002, 2021 | 39 | 2021 |
| Generalized normalizing flows via Markov chains PL Hagemann, J Hertrich, G Steidl Elements in Non-local Data Interactions: Foundations and Applications, 2023 | 23 | 2023 |
| PatchNR: learning from very few images by patch normalizing flow regularization F Altekrüger, A Denker, P Hagemann, J Hertrich, P Maass, G Steidl Inverse Problems 39 (6), 064006, 2023 | 21* | 2023 |
| Invertible neural networks versus MCMC for posterior reconstruction in grazing incidence X-ray fluorescence A Andrle, N Farchmin, P Hagemann, S Heidenreich, V Soltwisch, G Steidl International Conference on Scale Space and Variational Methods in Computer …, 2021 | 20 | 2021 |
| Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation P Hagemann, S Mildenberger, L Ruthotto, G Steidl, NT Yang arXiv preprint arXiv:2303.04772, 2023 | 18 | 2023 |
| Posterior sampling based on gradient flows of the MMD with negative distance kernel P Hagemann, J Hertrich, F Altekrüger, R Beinert, J Chemseddine, G Steidl arXiv preprint arXiv:2310.03054, 2023 | 11 | 2023 |
| Conditional generative models are provably robust: Pointwise guarantees for bayesian inverse problems F Altekrüger, P Hagemann, G Steidl arXiv preprint arXiv:2303.15845, 2023 | 10 | 2023 |
| Generative sliced MMD flows with Riesz kernels J Hertrich, C Wald, F Altekrüger, P Hagemann arXiv preprint arXiv:2305.11463, 2023 | 9 | 2023 |
| Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching J Chemseddine, P Hagemann, C Wald, G Steidl arXiv preprint arXiv:2403.18705, 2024 | 4* | 2024 |
| Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction M Piening, F Altekrüger, J Hertrich, P Hagemann, A Walther, G Steidl arXiv preprint arXiv:2312.16611, 2023 | 1 | 2023 |
| Mixed Noise and Posterior Estimation with Conditional DeepGEM P Hagemann, J Hertrich, M Casfor, S Heidenreich, G Steidl arXiv preprint arXiv:2402.02964, 2024 | | 2024 |
Gabriele SteidlTU Berlin在 math.tu-berlin.de 的电子邮件经过验证
