20 citations · 21 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
Antoine de Mathelin, François Deheeger, Mathilde Mougeot +1
This paper deals with uncertainty quantification and out-of-distribution detection in deep learning using Bayesian and ensemble methods. It proposes a practical solution to the lac…
cs.LG2021★ 20 cited
ADAPT : Awesome Domain Adaptation Python Toolbox
Antoine de Mathelin, Mounir Atiq, Guillaume Richard +5
In this paper, we introduce the ADAPT library, an open source Python API providing the implementation of the main transfer learning and domain adaptation methods. The library is de…