Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

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Statements (14)
Predicate Object
gptkbp:instanceOf gptkb:academic_journal
gptkbp:author gptkb:Zoubin_Ghahramani
gptkb:Yarin_Gal
gptkbp:citation high (over 5000 citations as of 2024)
gptkbp:contribution Proposes a method to estimate model uncertainty in deep learning
Interprets dropout in neural networks as approximate Bayesian inference
gptkbp:field gptkb:machine_learning
deep learning
https://www.w3.org/2000/01/rdf-schema#label Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
gptkbp:publicationYear 2016
gptkbp:publishedIn gptkb:International_Conference_on_Machine_Learning_(ICML)
gptkbp:url https://arxiv.org/abs/1506.02142
gptkbp:bfsParent gptkb:Yarin_Gal
gptkbp:bfsLayer 8