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Quantifying Predictive Uncertainty in Medical Image Analysis with Deep
  Kernel Learning

Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning

1 June 2021
Zhiliang Wu
Yinchong Yang
Jindong Gu
Volker Tresp
    UQCV
    MedIm
ArXivPDFHTML

Papers citing "Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning"

3 / 3 papers shown
Title
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in
  Gaussian Process Hybrid Deep Networks
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
John Bradshaw
A. G. Matthews
Zoubin Ghahramani
BDL
AAML
60
171
0
08 Jul 2017
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
282
9,136
0
06 Jun 2015
1