On the maximal cliques in c-max-tolerance graphs and their application in clustering molecular sequences. - Katharina Anna Lehmann; Michael Kaufmann 001; Stephan Steigele; Kay Nieselt (Algorithms Mol. Biol., 2006)

Uncertainty with deep learning: a practical view on out of distribution detection. - Daniel Siegismund; Stephan Heyse; Stephan Steigele (SDS, 2020)

Self-Supervised Representation Learning for High-Content Screening. - Daniel Siegismund; Mario Wieser; Stephan Heyse; Stephan Steigele (MIDL, 2022)

Vision Transformers Show Improved Robustness in High-Content Image Analysis. - Mario Wieser; Daniel Siegismund; Stephan Heyse; Stephan Steigele (SDS, 2022)

Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing. - Daniel Siegismund; Mario Wieser; Stephan Heyse; Stephan Steigele (DAGM, 2023)

PCIM: Learning Pixel Attributions via Pixel-wise Channel Isolation Mixing in High Content Imaging. - Daniel Siegismund; Mario Wieser; Stephan Heyse; Stephan Steigele (CoRR, 2024)

Revisiting Deep Archetypal Analysis for Phenotype Discovery in High Content Imaging. - Mario Wieser; Daniel Siegismund; Stephan Steigele (WACV, 2025)