11 citations · 11 across the 3 of their papers we have counts for
3 papers
Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection
Eduardo Dadalto, Florence Alberge, Pierre Duhamel +1
This paper introduces a universal approach to seamlessly combine out-of-distribution (OOD) detection scores. These scores encompass a wide range of techniques that leverage the sel…
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler +2
This paper tackles the challenge of detecting unreliable behavior in regression algorithms, which may arise from intrinsic variability (e.g., aleatoric uncertainty) or modeling err…
Igeood: An Information Geometry Approach to Out-of-Distribution Detection
Eduardo Dadalto Camara Gomes, Florence Alberge, Pierre Duhamel +1
Reliable out-of-distribution (OOD) detection is fundamental to implementing safer modern machine learning (ML) systems. In this paper, we introduce Igeood, an effective method for…