1 citations · 1 across the 2 of their papers we have counts for
3 papers
Improving Out-of-Distribution Detection by Combining Existing Post-hoc Methods
Paul Novello, Yannick Prudent, Joseba Dalmau +2
Since the seminal paper of Hendrycks et al. arXiv:1610.02136, Post-hoc deep Out-of-Distribution (OOD) detection has expanded rapidly. As a result, practitioners working on safety-c…
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)
Paul Novello, Joseba Dalmau, Léo Andeol
Research on Out-Of-Distribution (OOD) detection focuses mainly on building scores that efficiently distinguish OOD data from In Distribution (ID) data. On the other hand, Conformal…
GROOD: GRadient-Aware Out-of-Distribution Detection
Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot +2
Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models in real-world applications. Existing methods typically focus on feature represen…