2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2026
AP-OOD: Attention Pooling for Out-of-Distribution Detection
Claus Hofmann, Christian Huber, Bernhard Lehner +3
Out-of-distribution (OOD) detection, which maps high-dimensional data into a scalar OOD score, is critical for the reliable deployment of machine learning models. A key challenge i…
cs.LG2024★ 2 cited
Energy-based Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann, Simon Schmid, Bernhard Lehner +2
Out-of-distribution (OOD) detection is critical when deploying machine learning models in the real world. Outlier exposure methods, which incorporate auxiliary outlier data in the…