Determining Chess Game State from an Image. - Georg Wölflein; Ognjen Arandjelovic (J. Imaging, 2021)

HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks. - Georg Wölflein; In Hwa Um; David J. Harrison; Ognjen Arandjelovic (WACV, 2023)

Deep Multiple Instance Learning with Distance-Aware Self-Attention. - Georg Wölflein; Lucie Charlotte Magister; Pietro Liò; David J. Harrison; Ognjen Arandjelovic (CoRR, 2023)

A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology. - Georg Wölflein; Dyke Ferber; Asier Rabasco Meneghetti; Omar S. M. El Nahhas; Daniel Truhn; Zunamys I. Carrero; David J. Harrison; Ognjen Arandjelovic; Jakob Nikolas Kather (CoRR, 2023)

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)

Whole-Slide Images and Patches of Clear Cell Renal Cell Carcinoma Tissue Sections Counterstained with Hoechst 33342, CD3, and CD8 Using Multiple Immunofluorescence. - Georg Wölflein; In Hwa Um; David J. Harrison; Ognjen Arandjelovic (Data, 2023)

A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification. - Georg Wölflein; Dyke Ferber; Asier Rabasco Meneghetti; Omar S. M. El Nahhas; Daniel Truhn; Zunamys I. Carrero; David J. Harrison; Ognjen Arandjelovic; Jakob Nikolas Kather (ECCV Workshops (16), 2024)

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)

In-context learning enables multimodal large language models to classify cancer pathology images. - Dyke Ferber; Georg Wölflein; Isabella C. Wiest; Marta Ligero; Srividhya Sainath; Narmin Ghaffari Laleh; Omar S. M. El Nahhas; Gustav Müller-Franzes; Dirk Jäger; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2024)

Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology. - Dyke Ferber; Omar S. M. El Nahhas; Georg Wölflein; Isabella C. Wiest; Jan Clusmann; Marie-Elisabeth Leßman; Sebastian Foersch; Jacqueline Lammert; Maximilian Tschochohei; Dirk Jäger; Manuel Salto-Tellez; Nikolaus Schultz; et al. (CoRR, 2024)

End-To-End Clinical Trial Matching with Large Language Models. - Dyke Ferber; Lars Hilgers; Isabella C. Wiest; Marie-Elisabeth Leßmann; Jan Clusmann; Peter Neidlinger; Jiefu Zhu; Georg Wölflein; Jacqueline Lammert; Maximilian Tschochohei; Heiko Böhme; Dirk Jäger; et al. (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)

LLM Agents Making Agent Tools. - Georg Wölflein; Dyke Ferber; Daniel Truhn; Ognjen Arandjelovic; Jakob Nikolas Kather (ACL (1), 2025)

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