1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech
Shamira Venturini, Oliver Hennhöfer, Steffen Kinkel +1
Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent, and difficult to scale. We…
Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with nonconform
Oliver Hennhöfer, Oliver Hennhöfer, Maximilian Kirsch +1
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…