Under cold-start scarcity, ArcAD's Sinkhorn-balanced hyperspherical clustering plus anomaly-guided repulsion lifts reconstruction-based anomaly detection, with the clearest gains (+3.7 to +11.2 I-AUROC) on large multi-class benchmarks.
Advances in Neural Information Processing Systems 35, 4571–4584 (2022)
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LogiCo is a unified framework using component-level feature reconstruction to detect both logical and structural anomalies, achieving SOTA results on four benchmarks with code publicly available.
citing papers explorer
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ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection
Under cold-start scarcity, ArcAD's Sinkhorn-balanced hyperspherical clustering plus anomaly-guided repulsion lifts reconstruction-based anomaly detection, with the clearest gains (+3.7 to +11.2 I-AUROC) on large multi-class benchmarks.
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LogiCo: A Unified Framework for Logical and Structural Anomaly Detection
LogiCo is a unified framework using component-level feature reconstruction to detect both logical and structural anomalies, achieving SOTA results on four benchmarks with code publicly available.