Kamil Faber

Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios

Kamil Faber, Mateusz Smendowski, Roberto Corizzo

Continual anomaly detection (CAD) studies how models can adapt to evolving data distributions while retaining performance on previously observed regimes. CAD benchmarks, however, depend critically on how tasks are defined, filtered, ordered, and validated. In tabular domains, tas…Read more