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Equivariant Differentially Private Deep Learning


Jan 30, 2023
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis

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How Do Input Attributes Impact the Privacy Loss in Differential Privacy?


Nov 18, 2022
Tamara T. Mueller, Stefan Kolek, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Daniel Rueckert, Georgios Kaissis

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The Role of Local Alignment and Uniformity in Image-Text Contrastive Learning on Medical Images


Nov 14, 2022
Philip Müller, Georgios Kaissis, Daniel Rueckert

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* NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice 

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Exploiting segmentation labels and representation learning to forecast therapy response of PDAC patients


Nov 08, 2022
Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis

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Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens


Oct 24, 2022
Georgios Kaissis, Alexander Ziller, Stefan Kolek Martinez de Azagra, Daniel Rueckert

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Label Noise-Robust Learning using a Confidence-Based Sieving Strategy


Oct 11, 2022
Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis

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Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning


Sep 30, 2022
Reza Nasirigerdeh, Javad Torkzadehmahani, Daniel Rueckert, Georgios Kaissis

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Bridging the Gap: Differentially Private Equivariant Deep Learning for Medical Image Analysis


Sep 09, 2022
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis

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* Under review at GeoMedIA conference 

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Unsupervised Anomaly Localization with Structural Feature-Autoencoders


Aug 23, 2022
Felix Meissen, Johannes Paetzold, Georgios Kaissis, Daniel Rueckert

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* 10 pages, 5 figures, one table, accepted to the MICCAI 2021 BrainLes Workshop 

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Kernel Normalized Convolutional Networks


May 20, 2022
Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis

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