3 papers
cs.CV2026
Zero-Shot Test-Time Canonicalization using Out-of-Distribution Scoring
Dominik Lindner, Johann Schmidt, Tom Siegl +2
Pretrained vision models often misclassify inputs that are rotated, scaled, or sheared, even though these affine transformations leave the object class unchanged. Robustness is usu…
cs.LG2025
SubROC: AUC-Based Discovery of Exceptional Subgroup Performance for Binary Classifiers
Tom Siegl, Kutalmış Coşkun, Bjarne C. Hiller +3
Machine learning (ML) is increasingly employed in real-world applications like medicine or economics, thus, potentially affecting large populations. However, ML models often do not…
cs.LG2025
Informed, but Not Always Improved: Challenging the Benefit of Background Knowledge in GNNs
Kutalmış Coşkun, Ivo Kavisanczki, Amin Mirzaei +4
In complex and low-data domains such as biomedical research, incorporating background knowledge (BK) graphs, such as protein-protein interaction (PPI) networks, into graph-based ma…