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cs.LG2026
We Need to Rethink Benchmarking in Anomaly Detection
Philipp Röchner, Simon Klüttermann, Kevin Kammler +3
Despite the continuous proposal of new anomaly detection algorithms and extensive benchmarking efforts, progress seems to stagnate, with only minor performance differences between…
cs.LG2026
Evaluating Tabular Representation Learning for Network Intrusion Detection
Muhammad Usman Butt, Andreas Hotho, Daniel Schlör
Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. However, this approach require…
cs.LG2024
ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural Behavior
Melanie Schaller, Daniel Schlör, Andreas Hotho
External influences such as traffic and environmental factors induce vibrations in structures, leading to material degradation over time. These vibrations result in cracks due to t…