3 citations · 4 across the 9 of their papers we have counts for
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Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with nonconform
Oliver Hennhöfer, Maximilian Kirsch, Christine Preisach
Most anomaly detection systems output scores rather than calibrated decisions, leaving practitioners to choose thresholds heuristically and without clear statistical interpretation…
Between Resolution Collapse and Variance Inflation: Weighted Conformal Anomaly Detection in Low-Data Regimes
Oliver Hennhöfer, Christine Preisach
Standard conformal anomaly detection provides marginal finite-sample guarantees under the assumption of exchangeability . However, real-world data often exhibit distribution shifts…
Leave-One-Out-, Bootstrap- and Cross-Conformal Anomaly Detectors
Oliver Hennhöfer, Christine Preisach
The need for uncertainty quantification in anomaly detection systems has become increasingly important. In this context, effectively controlling Type I error rates without inflatin…