30 citations · 76 across the 19 of their papers we have counts for
3 papers · 1 filter
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…
A Meta-Generation framework for Industrial System Generation
Fouad Oubari, Raphael Meunier, Rodrigue Décatoire +1
Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a chea…
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification
Antoine de Mathelin, Francois Deheeger, Mathilde Mougeot +1
We consider the problem of uncertainty quantification in high dimensional regression and classification for which deep ensemble have proven to be promising methods. Recent observat…