| End-to-end privacy preserving deep learning on multi-institutional medical imaging G Kaissis, A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, ... Nature Machine Intelligence 3 (6), 473-484, 2021 | 258 | 2021 |
| Medical imaging deep learning with differential privacy A Ziller, D Usynin, R Braren, M Makowski, D Rueckert, G Kaissis Scientific Reports 11 (1), 13524, 2021 | 110 | 2021 |
| Adversarial interference and its mitigations in privacy-preserving collaborative machine learning D Usynin, A Ziller, M Makowski, R Braren, D Rueckert, B Glocker, ... Nature Machine Intelligence 3 (9), 749-758, 2021 | 41 | 2021 |
| SoK: Differential privacy on graph-structured data TT Mueller, D Usynin, JC Paetzold, D Rueckert, G Kaissis arXiv preprint arXiv:2203.09205, 2022 | 16 | 2022 |
| Differentially private graph classification with gnns TT Mueller, JC Paetzold, C Prabhakar, D Usynin, D Rueckert, G Kaissis arXiv preprint arXiv:2202.02575, 2022 | 15 | 2022 |
| Differentially private federated deep learning for multi-site medical image segmentation A Ziller, D Usynin, N Remerscheid, M Knolle, M Makowski, R Braren, ... arXiv preprint arXiv:2107.02586, 2021 | 14 | 2021 |
| Differentially private graph neural networks for whole-graph classification TT Mueller, JC Paetzold, C Prabhakar, D Usynin, D Rueckert, G Kaissis IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 12 | 2022 |
| Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning D Usynin, D Rueckert, J Passerat-Palmbach, G Kaissis Proceedings on Privacy Enhancing Technologies, 2022 | 11 | 2022 |
| Privacy-preserving medical image analysis A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, IDLC Junior, ... arXiv preprint arXiv:2012.06354, 2020 | 9 | 2020 |
| Beyond gradients: Exploiting adversarial priors in model inversion attacks D Usynin, D Rueckert, G Kaissis ACM Transactions on Privacy and Security 26 (3), 1-30, 2023 | 8 | 2023 |
| Complex-valued deep learning with differential privacy A Ziller, D Usynin, M Knolle, K Hammernik, D Rueckert, G Kaissis arXiv preprint arXiv:2110.03478, 2021 | 7 | 2021 |
| A unified interpretation of the gaussian mechanism for differential privacy through the sensitivity index G Kaissis, M Knolle, F Jungmann, A Ziller, D Usynin, D Rueckert arXiv preprint arXiv:2109.10528, 2021 | 6 | 2021 |
| Membership inference attacks against semantic segmentation models T Chobola, D Usynin, G Kaissis Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security …, 2023 | 5 | 2023 |
| Partial sensitivity analysis in differential privacy TT Mueller, A Ziller, D Usynin, M Knolle, F Jungmann, D Rueckert, ... arXiv preprint arXiv:2109.10582, 2021 | 3 | 2021 |
| Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation A Ziller, D Usynin, M Knolle, K Prakash, A Trask, R Braren, M Makowski, ... arXiv preprint arXiv:2107.04265, 2021 | 3 | 2021 |
| Differentially Private Guarantees for Analytics and Machine Learning on Graphs: A Survey of Results TT Mueller, D Usynin, JC Paetzold, R Braren, D Rueckert, G Kaissis Journal of Privacy and Confidentiality 14 (1), 2024 | 2 | 2024 |
| How Do Input Attributes Impact the Privacy Loss in Differential Privacy? TT Mueller, S Kolek, F Jungmann, A Ziller, D Usynin, M Knolle, ... arXiv preprint arXiv:2211.10173, 2022 | 2 | 2022 |
| Distributed Machine Learning and the Semblance of Trust D Usynin, A Ziller, D Rueckert, J Passerat-Palmbach, G Kaissis arXiv preprint arXiv:2112.11040, 2021 | 2 | 2021 |
| An automatic differentiation system for the age of differential privacy D Usynin, A Ziller, M Knolle, D Rueckert, G Kaissis arXiv preprint arXiv:2109.10573, 2021 | 2 | 2021 |
| Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty M Knolle, A Ziller, D Usynin, R Braren, MR Makowski, D Rueckert, ... arXiv preprint arXiv:2107.04296, 2021 | 2 | 2021 |
Georgios KaissisTechnical University of MunichVerified email at tum.de
