5 citations · 8 across the 3 of their papers we have counts for
3 papers
Bounding Box Anomaly Scoring for simple and efficient Out-of-Distribution detection
Mohamed Bahi Yahiaoui, Geoffrey Daniel, Loïc Giraldi +2
Out-of-distribution (OOD) detection aims to identify inputs that differ from the training distribution in order to reduce unreliable predictions by deep neural networks. Among post…
Deep Learning reconstruction with uncertainty estimation for photon interaction in fast scintillator detectors
Geoffrey Daniel, Mohamed Bahi Yahiaoui, Claude Comtat +7
This article presents a physics-informed deep learning method for the quantitative estimation of the spatial coordinates of gamma interactions within a monolithic scintillator, wit…
Packed-Ensembles for Efficient Uncertainty Estimation
Olivier Laurent, Adrien Lafage, Enzo Tartaglione +4
Deep Ensembles (DE) are a prominent approach for achieving excellent performance on key metrics such as accuracy, calibration, uncertainty estimation, and out-of-distribution detec…