Publications

Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis (2021). Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. arXiv preprint arXiv:2107.04265.

Tamara T Mueller, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Friederike Jungmann, Daniel Rueckert, Georgios Kaissis (2021). Partial sensitivity analysis in differential privacy. arXiv preprint arXiv:2109.10582.

Moritz Knolle, Dmitrii Usynin, Alexander Ziller, Marcus R Makowski, Daniel Rueckert, Georgios Kaissis (2021). NeuralDP Differentially private neural networks by design. arXiv preprint arXiv:2107.14582.

Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis (2021). Medical imaging deep learning with differential privacy. Scientific Reports.

Georgios Kaissis, Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann, Marc-Matthias Steinborn, others (2021). End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nature Machine Intelligence.

Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R Makowski, Daniel Rueckert, Georgios Kaissis (2021). Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. arXiv preprint arXiv:2107.04296.

Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis (2021). Differentially private federated deep learning for multi-site medical image segmentation. arXiv preprint arXiv:2107.02586.

Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis (2021). Complex-valued deep learning with differential privacy. arXiv preprint arXiv:2110.03478.

Dmitrii Usynin, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis (2021). An automatic differentiation system for the age of differential privacy. arXiv preprint arXiv:2109.10573.

Dmitrii Usynin, Alexander Ziller, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach (2021). Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. Nature Machine Intelligence.

Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert (2021). A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index. arXiv preprint arXiv:2109.10528.

Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus Makowski, Daniel Rueckert, Rickmer Braren, others (2020). Privacy-preserving medical image analysis. arXiv preprint arXiv:2012.06354.