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stat.ML2024
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity
Mouïn Ben Ammar, David Brellmann, Arturo Mendoza +2
Out-of-distribution (OOD) detection is essential for ensuring the reliability and safety of machine learning systems. In recent years, it has received increasing attention, particu…
stat.ML2023
NECO: NEural Collapse Based Out-of-distribution detection
Mouïn Ben Ammar, Nacim Belkhir, Sebastian Popescu +2
Detecting out-of-distribution (OOD) data is a critical challenge in machine learning due to model overconfidence, often without awareness of their epistemological limits. We hypoth…