3 papers
cs.LG2026
Why Ranking Anomaly Detection Algorithms Isn't as Reliable as You May Think
Simon Klüttermann, Jérôme Rutinowski, Frederik Polachowski +1
Anomaly detection is a safety-critical machine learning problem with applications ranging from fraud detection to network intrusion prevention and industrial monitoring. Despite th…
cs.CV2025
Enhancing Long-Term Re-Identification Robustness Using Synthetic Data: A Comparative Analysis
Christian Pionzewski, Rebecca Rademacher, Jérôme Rutinowski +5
This contribution explores the impact of synthetic training data usage and the prediction of material wear and aging in the context of re-identification. Different experimental set…
cond-mat.mtrl-sci2025
Extremely asymmetric diffraction as a method of determining magneto-optical constants for X-rays near absorption edges
M A Andreeva, Yu. Repchenko, A G Smekhova +3
The spectral dependence of the Bragg peak position under conditions of extremely asymmetric diffraction has been analyzed in the kinematical and dynamical approximations of the dif…