11 citations · 12 across the 5 of their papers we have counts for
3 papers · 1 filter
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…
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto, Marco Romanelli, Georg Pichler +1
Misclassification detection is an important problem in machine learning, as it allows for the identification of instances where the model's predictions are unreliable. However, con…
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…