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Calibrating Deep Neural Network Classifiers on Out-of-Distribution
  Datasets

Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets

16 June 2020
Zhihui Shao
Jianyi Yang
Shaolei Ren
    OODD
ArXivPDFHTML

Papers citing "Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets"

5 / 5 papers shown
Title
Gradient-free variational learning with conditional mixture networks
Gradient-free variational learning with conditional mixture networks
Conor Heins
Hao Wu
Dimitrije Marković
Alexander Tschantz
Jeff Beck
Christopher L. Buckley
BDL
29
2
0
29 Aug 2024
O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in
  Authorship Verification
O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification
Benedikt T. Boenninghoff
R. M. Nickel
D. Kolossa
OODD
32
12
0
30 Jun 2021
Graceful Degradation and Related Fields
Graceful Degradation and Related Fields
J. Dymond
31
4
0
21 Jun 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
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