Partial sensitivity analysis in differential privacy. - Tamara T. Mueller; Alexander Ziller; Dmitrii Usynin; Moritz Knolle; Friederike Jungmann; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

Differentially Private Graph Classification with GNNs. - Tamara T. Mueller; Johannes C. Paetzold; Chinmay Prabhakar; Dmitrii Usynin; Daniel Rueckert; Georgios Kaissis (CoRR, 2022)

SoK: Differential Privacy on Graph-Structured Data. - Tamara T. Mueller; Dmitrii Usynin; Johannes C. Paetzold; Daniel Rueckert; Georgios Kaissis (CoRR, 2022)

How Do Input Attributes Impact the Privacy Loss in Differential Privacy? - Tamara T. Mueller; Stefan Kolek; Friederike Jungmann; Alexander Ziller; Dmitrii Usynin; Moritz Knolle; Daniel Rueckert; Georgios Kaissis (CoRR, 2022)

Privacy: An Axiomatic Approach. - Alexander Ziller; Tamara T. Mueller; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (Entropy, 2022)

Gradient Self-alignment in Private Deep Learning. - David Bani-Harouni; Tamara T. Mueller; Daniel Rueckert; Georgios Kaissis (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression. - Kyriaki-Margarita Bintsi; Tamara T. Mueller; Sophie Starck; Vasileios Baltatzis; Alexander Hammers; Daniel Rueckert (GRAIL/OCELOT@MICCAI, 2023)

Extended Graph Assessment Metrics for Regression and Weighted Graphs. - Tamara T. Mueller; Sophie Starck; Leonhard F. Feiner; Kyriaki-Margarita Bintsi; Daniel Rueckert; Georgios Kaissis (GRAIL/OCELOT@MICCAI, 2023)

Body Fat Estimation from Surface Meshes Using Graph Neural Networks. - Tamara T. Mueller; Siyu Zhou; Sophie Starck; Friederike Jungmann; Alexander Ziller; Orhun Aksoy; Danylo Movchan; Rickmer Braren; Georgios Kaissis; Daniel Rueckert (ShapeMI@MICCAI, 2023)

Explainable 2D Vision Models for 3D Medical Data. - Alexander Ziller; Alp Güvenir; Ayhan Can Erdur; Tamara T. Mueller; Philip Müller; Friederike Jungmann; Johannes Brandt; Jan Peeken; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (CoRR, 2023)

Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure. - Tamara T. Mueller; Maulik Chevli; Ameya Daigavane; Daniel Rueckert; Georgios Kaissis (CoRR, 2023)

Atlas-Based Interpretable Age Prediction. - Sophie Starck; Yadunandan Vivekanand Kini; Jessica Johanna Maria Ritter; Rickmer Braren; Daniel Rueckert; Tamara T. Mueller (CoRR, 2023)

Extended Graph Assessment Metrics for Graph Neural Networks. - Tamara T. Mueller; Sophie Starck; Leonhard F. Feiner; Kyriaki-Margarita Bintsi; Daniel Rueckert; Georgios Kaissis (CoRR, 2023)

Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging. - Alexander Ziller; Tamara T. Mueller; Simon Stieger; Leonhard F. Feiner; Johannes Brandt; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (CoRR, 2023)

Differentially Private Graph Neural Networks for Whole-Graph Classification. - Tamara T. Mueller; Johannes C. Paetzold; Chinmay Prabhakar; Dmitrii Usynin; Daniel Rueckert; Georgios Kaissis (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Differentially Private Graph Neural Networks for Medical Population Graphs and The Impact of The Graph Structure. - Tamara T. Mueller; Maulik Chevli; Ameya Daigavane; Daniel Rueckert; Georgios Kaissis (ISBI, 2024)

Bounding Reconstruction Attack Success of Adversaries Without Data Priors. - Alexander Ziller; Anneliese Riess; Kristian Schwethelm; Tamara T. Mueller; Daniel Rueckert; Georgios Kaissis (CoRR, 2024)

Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases. - Sophie Starck; Vasiliki Sideri-Lampretsa; Bernhard Kainz; Martin J. Menten; Tamara T. Mueller; Daniel Rueckert (CoRR, 2024)

Differentially Private Guarantees for Analytics and Machine Learning on Graphs: A Survey of Results. - Tamara T. Mueller; Dmitrii Usynin; Johannes C. Paetzold; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (J. Priv. Confidentiality, 2024)

Reconciling privacy and accuracy in AI for medical imaging. - Alexander Ziller; Tamara T. Mueller; Simon Stieger; Leonhard F. Feiner; Johannes Brandt; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (Nat. Mac. Intell., 2024)

A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations. - Tamara T. Mueller; Sophie Starck; Alina Dima; Stephan Wunderlich; Kyriaki-Margarita Bintsi; Kamilia Zaripova; Rickmer Braren; Daniel Rueckert; Anees Kazi; Georgios Kaissis (Trans. Mach. Learn. Res., 2024)

Are Population Graphs Really as Powerful as Believed? - Tamara T. Müller; Sophie Starck; Kyriaki-Margarita Bintsi; Alexander Ziller; Rickmer Braren; Georgios Kaissis; Daniel Rueckert (Trans. Mach. Learn. Res., 2024)

Large-scale UK Biobank Whole Body Atlases. - Sophie Starck; Vasiliki Sideri-Lampretsa; Jessica Johanna Maria Ritter; Veronika A. Zimmer; Rickmer Braren; Tamara T. Mueller; Daniel Rueckert (Zenodo, 2024)

AI-driven preclinical disease risk assessment using imaging in UK biobank. - Dmitrii Seletkov; Sophie Starck; Tamara T. Mueller; Yundi Zhang; Lisa Steinhelfer; Daniel Rueckert; Rickmer Braren (npj Digit. Medicine, 2025)

Parametric shape models for vessels learned from segmentations via differentiable voxelization. - Alina F. Dima; Suprosanna Shit; Huaqi Qiu; Robbie Holland; Tamara T. Mueller; Fabio Musio; Kaiyuan Yang 003; Bjoern H. Menze; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert (CoRR, 2025)