1 citations · 1 across the 2 of their papers we have counts for
4 papers
Deep Sturm--Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune +1
Although Artificial Neural Networks (ANNs) have achieved remarkable success across various tasks, they still suffer from limited generalization. We hypothesize that this limitation…
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…
Conformal Semantic Image Segmentation: Post-hoc Quantification of Predictive Uncertainty
Luca Mossina, Joseba Dalmau, Léo andéol
We propose a post-hoc, computationally lightweight method to quantify predictive uncertainty in semantic image segmentation. Our approach uses conformal prediction to generate stat…
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…