Measured Composite Collision Models: Quantum Trajectory Purities and Channel Divisibility. - Konstantin Beyer; Kimmo Luoma; Tim Lenz; Walter T. Strunz (Entropy, 2022)

From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology. - Omar S. M. El Nahhas; Marko van Treeck; Georg Wölflein; Michaela Unger; Marta Ligero; Tim Lenz; Sophia J. Wagner; Katherine Jane Hewitt; Firas Khader; Sebastian Foersch; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2023)

Joint Multi-task Learning Improves Weakly-Supervised Biomarker Prediction in Computational Pathology. - Omar S. M. El Nahhas; Georg Wölflein; Marta Ligero; Tim Lenz; Marko van Treeck; Firas Khader; Daniel Truhn; Jakob Nikolas Kather (MICCAI (4), 2024)

Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology. - Tim Lenz; Omar S. M. El Nahhas; Marta Ligero; Jakob Nikolas Kather (CoRR, 2024)

Benchmarking foundation models as feature extractors for weakly-supervised computational pathology. - Peter Neidlinger; Omar S. M. El Nahhas; Hannah Sophie Muti; Tim Lenz; Michael Hoffmeister; Hermann Brenner; Marko van Treeck; Rupert Langer; Bastian Dislich; Hans-Michael Behrens; Christoph Röcken; Sebastian Foersch; et al. (CoRR, 2024)

Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation. - Volodymyr Shcherbyna; Linh Kästner; Diego Diaz; Huu Giang Nguyen; Maximilian Ho-Kyoung Schreff; Tim Lenz; Jonas Kreutz; Ahmed Martban; Huajian Zeng; Harold Soh (CoRR, 2024)

Abnormality-Driven Representation Learning for Radiology Imaging. - Marta Ligero; Tim Lenz; Georg Wölflein; Omar S. M. El Nahhas; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2024)

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning. - Tim Lenz; Peter Neidlinger; Marta Ligero; Georg Wölflein; Marko van Treeck; Jakob Nikolas Kather (CVPR, 2025)

A deep learning framework for efficient pathology image analysis. - Peter Neidlinger; Tim Lenz; Sebastian Foersch; Chiara Maria Lavinia Loeffler; Jan Clusmann; Marco Gustav; Lawrence A. Shaktah; Rupert Langer; Bastian Dislich; Lisa A. Boardman; Amy J. French; Ellen L. Goode; et al. (CoRR, 2025)

Three-dimensional end-to-end deep learning for brain MRI analysis. - Radhika Juglan; Marta Ligero; Zunamys I. Carrero; Asier Rabasco Meneghetti; Tim Lenz; Leo Misera; Gregory Patrick Veldhuizen; Paul Kuntke; Hagen H. Kitzler; Sven Nebelung; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2025)