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Detecting Misclassification Errors in Neural Networks with a Gaussian
  Process Model

Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model

5 October 2020
Xin Qiu
Risto Miikkulainen
ArXivPDFHTML

Papers citing "Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model"

3 / 3 papers shown
Title
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Arthur Pignet
Chiara Regniez
John Klein
72
1
0
30 Oct 2024
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han
Mengmi Zhang
119
0
0
03 Oct 2024
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
9,138
0
06 Jun 2015
1