Dynamic Distribution Shifts: OoD Detection with Dynamic Thresholds H/F - Palaiseau - France, Ile-de-France, Essonne ()

Réservé aux membres inscrits Palaiseau - France, Ile-de-France, Essonne ()

il y a 1 heure

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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.


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