| PRECODE-A Generic Model Extension to Prevent Deep Gradient Leakage D Scheliga, P Mäder, M Seeland Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 34 | 2022 |
| Dropout is NOT All You Need to Prevent Gradient Leakage D Scheliga, P Mäder, M Seeland Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9733-9741, 2023 | 5 | 2023 |
| Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage D Scheliga, P Mäder, M Seeland arXiv preprint arXiv:2208.04767, 2022 | 1 | 2022 |
| Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks D Scheliga, P Mäder, M Seeland arXiv preprint arXiv:2309.04515, 2023 | | 2023 |
| Model-based data generation for the evaluation of functional reliability and resilience of distributed machine learning systems against abnormal cases R Altschaffel, J Dittmann, D Scheliga, M Seeland, P Mäder Engineering for a Changing World: Proceedings; 60th ISC, Ilmenau Scientific …, 2023 | | 2023 |
| PRECODE-A Generic Model Extension to Prevent Deep Gradient Leakage–Supplementary Material– D Scheliga, P Mäder, M Seeland | | |
