Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
GPTKB entity
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 |
| 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 |
9
|
| https://www.w3.org/2000/01/rdf-schema#label |
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
|