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cs.LG2025
PRIVET: PRoximIty leakage detection Via Extreme value Theory
Antoine Szatkownik, Aurélien Decelle, Beatriz Seoane +7
Deep generative models are often trained on sensitive data, such as genetic sequences, health data, or more broadly, any copyrighted, licensed or protected content. This raises cri…
cs.LG2025★ 1 cited
A theoretical framework for overfitting in energy-based modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner +1
We investigate the impact of limited data on training pairwise energy-based models for inverse problems aimed at identifying interaction networks. Utilizing the Gaussian model as t…