Dynamic Distribution Shifts: OoD Detection with Dynamic Thresholds H/F - Palaiseau - France, Ile-de-France, Essonne ()
il y a 1 heure
Job summary
The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented in the training data and can naturally arrive during deployment.
Description du poste
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