| Fully Hyperbolic Convolutional Neural Networks for Computer Vision A Bdeir, K Schwethelm, N Landwehr The Twelfth International Conference on Learning Representations, 2024 | 32* | 2024 |
| Differentially Private Active Learning: Balancing Effective Data Selection and Privacy K Schwethelm, J Kaiser, J Kuntzer, M Yiğitsoy, D Rückert, G Kaissis 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 858-878, 2025 | 1 | 2025 |
| Visual Privacy Auditing with Diffusion Models K Schwethelm, J Kaiser, M Knolle, S Lockfisch, D Rueckert, A Ziller Transactions on Machine Learning Research (TMLR), 2025 | | 2025 |
| Laplace Sample Information: Data Informativeness Through a Bayesian Lens J Kaiser, K Schwethelm, D Rueckert, G Kaissis The Thirteenth International Conference on Learning Representations, 2025 | | 2025 |
| Bounding Reconstruction Attack Success of Adversaries Without Data Priors A Ziller, A Riess, K Schwethelm, TT Mueller, D Rueckert, G Kaissis arXiv preprint arXiv:2402.12861, 2024 | | 2024 |
Daniel RueckertTechnical University of Munich and Imperial College Londontum.de üzerinde doğrulanmış e-posta adresine sahip