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Deep learning models frequently make incorrect predictions with high confidence when presented with test examples that are not well represented in their training dataset.
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks and Thomas Dietterich · 1903
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Nguyen, Jason Yosinski, and Jeff Clune · 2014
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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Yarin Gal and Zoubin Ghahramani · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Concrete Problems in AI Safety
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané · 2016
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A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks and Kevin Gimpel · 2016
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Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alex Alemi · 2016
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Synthesizing Robust Adversarial Examples
Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok · 2017
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Detecting Adversarial Samples from Artifacts
Reuben Feinman, Ryan R. Curtin, Saurabh Shintre, and Andrew B. Gardner · 2017
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On Calibration of Modern Neural Networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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Adversarial Attacks on Neural Network Policies
Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, and Pieter Abbeel · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
Kimin Lee, Honglak Lee, Kibok Lee, and Jinwoo Shin · 2017
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Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang, Yixuan Li, and R. Srikant · 2017
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To Trust Or Not To Trust A Classifier
Heinrich Jiang, Been Kim, Melody Y. Guan, and Maya Gupta · 2018
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A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Predictive uncertainty estimation via prior networks
Andrey Malinin and Mark Gales · 2018
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Do Deep Generative Models Know What They Don’t Know?
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, and Balaji Lakshminarayanan · 2018
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Classification Uncertainty of Deep Neural Networks Based on Gradient Information
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Prototypical Networks for Few-shot Learning
Jake Snell, Kevin Swersky, and Richard S. Zemel · 2017
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Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola · 2017
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Learning Confidence for Out-of-Distribution Detection in Neural Networks
Terrance DeVries and Graham W. Taylor · 2018
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Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, and S. M. Ali Eslami · 2018
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Reliable uncertainty estimates in deep neural networks using noise contrastive priors
Danijar Hafner, Dustin Tran, Alex Irpan, Timothy Lillicrap, and James Davidson · 2018
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Yotam Hechtlinger, Barnabas Poczos, and Larry Wasserman · 2018
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Philipp Oberdiek, Matthias Rottmann, and Hanno Gottschalk · 2018
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Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband, John Aslanides, and Albin Cassirer · 2018
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Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot and Patrick McDaniel · 2018
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Evidential deep learning to quantify classification uncertainty
Murat Sensoy, Lance Kaplan, and Melih Kandemir · 2018
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Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Jonathan Uesato, Brendan O’Donoghue, Aaron van den Oord, and Pushmeet Kohli · 2018
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Do imagenet classifiers generalize to imagenet?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar · 2019
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