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Georgios Kaissis

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How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection

Dec 06, 2023
Felix Meissen, Johannes Getzner, Alexander Ziller, Georgios Kaissis, Daniel Rueckert

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Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging

Dec 05, 2023
Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis

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SoK: Memorisation in machine learning

Nov 06, 2023
Dmitrii Usynin, Moritz Knolle, Georgios Kaissis

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Propagation and Attribution of Uncertainty in Medical Imaging Pipelines

Sep 28, 2023
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis

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(Predictable) Performance Bias in Unsupervised Anomaly Detection

Sep 25, 2023
Felix Meissen, Svenja Breuer, Moritz Knolle, Alena Buyx, Ruth Müller, Georgios Kaissis, Benedikt Wiestler, Daniel Rückert

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MAD: Modality Agnostic Distance Measure for Image Registration

Sep 06, 2023
Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu, Georgios Kaissis, Daniel Rueckert

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Anatomy-Driven Pathology Detection on Chest X-rays

Sep 05, 2023
Philip Müller, Felix Meissen, Johannes Brandt, Georgios Kaissis, Daniel Rueckert

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Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD

Aug 23, 2023
Moritz Knolle, Robert Dorfman, Alexander Ziller, Daniel Rueckert, Georgios Kaissis

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Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure

Jul 13, 2023
Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis

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Extended Graph Assessment Metrics for Graph Neural Networks

Jul 13, 2023
Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis

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