2 citations · 2 across the 3 of their papers we have counts for
3 papers
Stylized Meta-Album: Group-bias injection with style transfer to study robustness against distribution shifts
Romain Mussard, Aurélien Gauffre, Ihsan Ullah +4
We introduce Stylized Meta-Album (SMA), a new image classification meta-dataset comprising 24 datasets (12 content datasets, and 12 stylized datasets), designed to advance studies…
Multi-Label Contrastive Learning : A Comprehensive Study
Alexandre Audibert, Aurélien Gauffre, Massih-Reza Amini
Multi-label classification, which involves assigning multiple labels to a single input, has emerged as a key area in both research and industry due to its wide-ranging applications…
A Unified Contrastive Loss for Self-Training
Aurelien Gauffre, Julien Horvat, Massih-Reza Amini
Self-training methods have proven to be effective in exploiting abundant unlabeled data in semi-supervised learning, particularly when labeled data is scarce. While many of these a…