Publications
Tim Tomov, Dominik Fuchsgruber, Tom Wollschläger, Stephan Günnemann (2025). The Illusion of Certainty: Uncertainty quantification for LLMs fails under ambiguity.
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Jan C. Peeken, Lucas Etzel, Tim Tomov, Stefan Münch, Lars Schüttrumpf, Julius H. Shaktour, Johannes Kiechle, Carolin Knebel, Stephanie K. Schaub, Nina A. Mayr, Henry C. Woodruff, Philippe Lambin, Alexandra S. Gersing, Denise Bernhardt, Matthew J. Nyflot, Bjoern Menze, Stephanie E. Combs, Fernando Navarro (2024). Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.
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Projects

Learning with Kernels

This project provides a comprehensive introduction to kernel methods in machine learning. It covers the theoretical foundations as well as practical aspects such as Support Vector Machines (SVMs) and scalable techniques like Random Fourier Features.

Novel View Synthesis for Scenes in the Wild

We propose a novel combination of local as well as global conditioning modules with which we finetune Stable Diffusion on the ScanNet++ dataset.