Towards principled continual anomaly detection: a systematic framework and benchmark scenarios
Read the original at arxiv.org→arXiv:2607.18289v1 Announce Type: new Abstract: Continual anomaly detection (CAD) studies how models can adapt to evolving data distributions while retaining performance on previously observed regimes. CAD...
Original headline: "Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios"