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Improving Classifier Confidence using Lossy Label-Invariant
  Transformations

Improving Classifier Confidence using Lossy Label-Invariant Transformations

9 November 2020
Sooyong Jang
Insup Lee
James Weimer
    UQCV
ArXivPDFHTML

Papers citing "Improving Classifier Confidence using Lossy Label-Invariant Transformations"

5 / 5 papers shown
Title
Exploring Covariate and Concept Shift for Detection and Calibration of
  Out-of-Distribution Data
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
Junjiao Tian
Yen-Change Hsu
Yilin Shen
Hongxia Jin
Z. Kira
OODD
19
6
0
28 Oct 2021
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
74
268
0
13 Jun 2018
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
276
5,675
0
05 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,225
0
16 Nov 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
9,145
0
06 Jun 2015
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