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In this paper we establish rigorous benchmarks for image classifier robustness.
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“Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift”
Sergey Ioffe and Christian Szegedy · 2015
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“Measuring Neural Net Robustness with Constraints”
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Nicholas Carlini and David Wagner · 2016
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Nicholas Carlini and David Wagner · 2016
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“Densely connected convolutional networks”
Gao Huang, Zhuang Liu, Laurens van Maaten and Kilian Weinberger · 2017
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“Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization”
Xun Huang and Serge Belongie · 2017
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“Towards Proving the Adversarial Robustness of Deep Neural Networks”
Guy Katz et al · 2017
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“Multigrid Neural Architectures”
Tsung-Wei Ke, Michael Maire and Stella. Yu · 2017
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“Adversarial Machine Learning at Scale”
Alexey Kurakin, Ian Goodfellow and Samy Bengio · 2017
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“SGDR: Stochastic Gradient Descent with Warm Restarts”
Ilya Loshchilov and Frank Hutter · 2017
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Peva Blanchard, El Mhamdi, Rachid Guerraoui and Julien Stainer · 2017
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“Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods”
Nicholas Carlini and David Wagner · 2017
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“Ground-Truth Adversarial Examples”, 2017
Nicholas Carlini, Guy Katz, Clark Barrett and David. Dill · 2017
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“A Study and Comparison of Human and Deep Learning Recognition Performance Under Visual Distortions”, 2017
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“Quality Resilient Deep Neural Networks”, 2017
Samuel Dodge and Lina Karam · 2017
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“Standard detectors aren’t (currently) fooled by physical adversarial stop signs”, 2017
Jiajun Lu, Hussein Sibai, Evan Fabry and David Forsyth · 2017
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“On Detecting Adversarial Perturbations”
Jan Metzen, Tim Genewein, Volker Fischer and Bastian Bischoff · 2017
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“Robust features in Deep Learning based Speech Recognition”
Vikramjit Mitra et al · 2017
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“Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks”, 2017
Nicolas Papernot et al · 2017
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“Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models”, 2017
Jonas Rauber, Wieland Brendel and Matthias Bethge · 2017
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“Certified Defenses for Data Poisoning Attacks”
Jacob Steinhardt, Pang Koh and Percy Liang · 2017
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