Moritz Knolle

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 15

Top Topics

Differential Privacy

Sensitivity Analysis

Diffusion Models

Unsupervised Anomaly Detection

Top Venues

J. Priv. Confidentiality

Publications

Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Daniel Rueckert, Georgios Kaissis, Alexander Ziller
Visual Privacy Auditing with Diffusion Models. CoRR (2024)
Dmitrii Usynin, Moritz Knolle, Georgios Kaissis
SoK: Memorisation in machine learning. CoRR (2023)
Felix Meissen, Svenja Breuer, Moritz Knolle, Alena Buyx, Ruth Müller, Georgios Kaissis, Benedikt Wiestler, Daniel Rueckert
(Predictable) Performance Bias in Unsupervised Anomaly Detection. CoRR (2023)
Moritz Knolle, Robert Dorfman, Alexander Ziller, Daniel Rueckert, Georgios Kaissis
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD. CoRR (2023)
Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert
Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index. J. Priv. Confidentiality 12 (1) (2022)
Tamara T. Mueller, Stefan Kolek, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Daniel Rueckert, Georgios Kaissis
How Do Input Attributes Impact the Privacy Loss in Differential Privacy? CoRR (2022)
Moritz Knolle, Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
NeuralDP Differentially private neural networks by design. CoRR (2021)
Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index. CoRR (2021)
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR (2021)
Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Differentially private federated deep learning for multi-site medical image segmentation. CoRR (2021)
Dmitrii Usynin, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis
An automatic differentiation system for the age of differential privacy. CoRR (2021)
Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. CoRR (2021)
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis
Complex-valued deep learning with differential privacy. CoRR (2021)
Tamara T. Mueller, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Friederike Jungmann, Daniel Rueckert, Georgios Kaissis
Partial sensitivity analysis in differential privacy. CoRR (2021)
Moritz Knolle, Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, Daniel Sasse, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren
Efficient, high-performance pancreatic segmentation using multi-scale feature extraction. CoRR (2020)