Evidential deep learning for uncertainty quantification and out-of-distribution detection in jet identification using deep neural networks
Current methods commonly used for uncertainty quantification (UQ) in deep learning (DL) models utilize Bayesian methods which are computationally expensive and time-consuming. In this paper, we provide a detailed study of UQ based on evidential DL (EDL) for deep neural network models designed to ide...
| Published in: | Machine Learning: Science and Technology |
|---|---|
| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-2153/ade51b |
