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1903.12261
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Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
28 March 2019
Dan Hendrycks
Thomas G. Dietterich
OOD
VLM
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Papers citing
"Benchmarking Neural Network Robustness to Common Corruptions and Perturbations"
13 / 113 papers shown
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Aggregated Residual Transformations for Deep Neural Networks
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Ross B. Girshick
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Adversarial Machine Learning at Scale
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A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
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Kevin Gimpel
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07 Oct 2016
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
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25 Aug 2016
Early Methods for Detecting Adversarial Images
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Kevin Gimpel
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01 Aug 2016
Defensive Distillation is Not Robust to Adversarial Examples
Nicholas Carlini
D. Wagner
56
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14 Jul 2016
Measuring Neural Net Robustness with Constraints
Osbert Bastani
Yani Andrew Ioannou
Leonidas Lampropoulos
Dimitrios Vytiniotis
A. Nori
A. Criminisi
AAML
89
424
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24 May 2016
Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng
Yang Song
Thomas Leung
Ian Goodfellow
OOD
50
638
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15 Apr 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
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10 Dec 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot
Patrick McDaniel
Xi Wu
S. Jha
A. Swami
AAML
113
3,072
0
14 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
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463
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0
11 Feb 2015
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
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277
14,927
1
21 Dec 2013
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