97 citations · 161 across the 13 of their papers we have counts for
Showing 2021Show all
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cs.LG2021★ 26 cited
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Rame, Corentin Dancette, Matthieu Cord
Learning robust models that generalize well under changes in the data distribution is critical for real-world applications. To this end, there has been a growing surge of interest…
cs.LG2021
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks
Alexandre Rame, Remy Sun, Matthieu Cord
Recent strategies achieved ensembling "for free" by fitting concurrently diverse subnetworks inside a single base network. The main idea during training is that each subnetwork lea…
cs.LG2021★ 6 cited
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Alexandre Rame, Matthieu Cord
Deep ensembles perform better than a single network thanks to the diversity among their members. Recent approaches regularize predictions to increase diversity; however, they also…