Teaching
Cascade Learning for Group-Specific Medicine: A Multi-Stage Approach
WS24/25 Practical: Applied Deep Learning in Medicine
Computer-aided diagnosis systems are a powerful tool for physicians to support the identification of diseases in medical images.
TUM, Munich, Germany
April 01, 2025
April 01, 2025
Addressing Accuracy-Fairness Trade-off via Laplace Approximation Methods
Master Thesis
The increasing deployment of machine learning models in critical domains such as finance, criminal justice, and healthcare has raised concerns about the ethical implications of ...
TUM, Munich, Germany
April 01, 2025
April 01, 2025
Rotation Equivariant ProtoPNets in Medicine
SS24 Practical: Applied Deep Learning in Medicine
ReProtoPNet is a novel AI model specifically designed to enhance both the interpretability and rotation invariance of machine learning systems, particularly for crucial medical ...
TUM, Munich, Germany
October 01, 2024
October 01, 2024
Reconstruction attacks on Genetic Data
WS23/24 Practical: Applied Deep Learning in Medicine
This work shows that training data with higher spatial correlation, such as medical images, is more vulnerable to gray-box model inversion attacks than unstructured data like ge...
TUM, Munich, Germany
April 01, 2024
April 01, 2024