3 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
-JEPA Spectral Anti-Collapse Regularization for Self-Supervised Learning
Berker Demirel, Clémentine Dominé, Valentino Maiorca +3
Joint-embedding self-supervised learning typically combines an invariance objective across augmented views with additional mechanisms to prevent representational collapse. These ob…
Assessing Sample Quality in Conditional Generation under Compositional Shift
Berker Demirel, Valentino Maiorca, Marco Fumero +2
Conditional generators provide a natural tool for controllable generation, including settings where the desired condition is a new composition of observed attributes or experimenta…
Adjusting Pretrained Backbones for Performativity
Berker Demirel, Lingjing Kong, Kun Zhang +3
With the widespread deployment of deep learning models, they influence their environment in various ways. The induced distribution shifts can lead to unexpected performance degrada…
Out-of-Distribution Detection with Relative Angles
Berker Demirel, Marco Fumero, Francesco Locatello
Deep learning systems deployed in real-world applications often encounter data that is different from their in-distribution (ID). A reliable model should ideally abstain from makin…
ADRMX: Additive Disentanglement of Domain Features with Remix Loss
Berker Demirel, Erchan Aptoula, Huseyin Ozkan
The common assumption that train and test sets follow similar distributions is often violated in deployment settings. Given multiple source domains, domain generalization aims to c…