3 citations · 7 across the 8 of their papers we have counts for
3 papers · 1 filter
Test-Time Adaptation with Principal Component Analysis
Thomas Cordier, Victor Bouvier, Gilles Hénaff +1
Machine Learning models are prone to fail when test data are different from training data, a situation often encountered in real applications known as distribution shift. While sti…
Towards Clear Expectations for Uncertainty Estimation
Victor Bouvier, Simona Maggio, Alexandre Abraham +1
If Uncertainty Quantification (UQ) is crucial to achieve trustworthy Machine Learning (ML), most UQ methods suffer from disparate and inconsistent evaluation protocols. We claim th…
Performance Prediction Under Dataset Shift
Simona Maggio, Victor Bouvier, Léo Dreyfus-Schmidt
ML models deployed in production often have to face unknown domain changes, fundamentally different from their training settings. Performance prediction models carry out the crucia…