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We evaluate the uncertainty quality in neural networks using anomaly detection.
An introduction to the bootstrap
Bradley Efron and Robert J Tibshirani · 1994
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The mnist database of handwritten digits, 1998
Yann LeCun, Corinna Cortes, and Christopher JC Burges · 1998
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Pattern recognition
Christopher M Bishop · 2006
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Cross-validation
Payam Refaeilzadeh, Lei Tang, and Huan Liu · 2009
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan
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Variational dropout and the local reparameterization trick
Diederik P Kingma, Tim Salimans, and Max Welling · 2015
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Early stopping is nonparametric variational inference
Dougal Maclaurin, David Duvenaud, and Ryan P Adams · 2015
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Bayesian convolutional neural networks with bernoulli approximate variational inference
Yarin Gal and Zoubin Ghahramani · 2015
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The inescapability of uncertainty: Ai, uncertainty, and why you should vote no matter what predictions say
Jennifer Vaughan and Hanna Wallach · 2016
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Artificial intelligence’s white guy problem
Kate Crawford · 2016
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Uncertainty in Deep Learning
Yarin Gal · 2016
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Stan: A probabilistic programming language
Bob Carpenter, Andrew Gelman, Matt Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Michael A Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell · 2016
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Weight uncertainty in neural network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra · 2015
Cited alongside, same era.