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Perhaps surprisingly, recent studies have shown probabilistic model likelihoods have poor specificity for out-of-distribution (OOD) detection and often assign higher likelihoods to OOD data than in-distribution data.
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Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, and Balaji Lakshminarayanan · 1906
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Christopher M Bishop · 1994
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Antonio Torralba, Rob Fergus, and William T Freeman · 2008
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Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and R. Srikant · 2018
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Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Łukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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Likelihood ratios for out-of-distribution detection
Jie Ren, Peter J Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark Depristo, Joshua Dillon, and Balaji Lakshminarayanan · 2019
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Input complexity and out-of-distribution detection with likelihood-based generative models
Joan Serrà, David Álvarez, Vicenç Gómez, Olga Slizovskaia, José F Núñez, and Jordi Luque · 2019
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Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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Uncertainty in the variational information bottleneck
Alexander A Alemi, Ian Fischer, and Joshua V Dillon · 2018
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Waic, but why? generative ensembles for robust anomaly detection
Hyunsun Choi, Eric Jang, and Alexander A Alemi · 2018
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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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Akshay Raj Dhamija, Manuel Günther, and Terrance Boult · 2018
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Diederik P. Kingma and Prafulla Dhariwal · 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
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Confidence-calibrated adversarial training: Generalizing to unseen attacks
David Stutz, Matthias Hein, and Bernt Schiele · 2019
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