← Search

Florence Alberge

2 accepted papers

2024

Beyond the Norms: Detecting Prediction Errors in Regression Models

ICML 2024spotlight

This paper tackles the challenge of detecting unreliable behavior in regression algorithms, which may arise from intrinsic variability (e.g., aleatoric uncertainty) or modeling errors (e.g., model uncertainty). First, we formally introduce the notion of unreliability in regression, i.e., when the ou…

Cited by 0SourcePDFScholar
2022

Igeood: An Information Geometry Approach to Out-of-Distribution Detection

ICLR 2022poster

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 detecting OOD samples. Igeood applies to any pre-trained neural network, works under various degrees of access to the M…