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The discovery of adversarial examples has raised concerns about the practical deployment of deep learning systems.
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Synthesizing Robust Adversarial Examples
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Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Anish Athalye, Nicholas Carlini, and David Wagner. 2018 · 2018
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Thermometer encoding: One hot way to resist adversarial examples. In International Conference on Learning Representations
Jacob Buckman, Aurko Roy, Colin Raffel, and Ian Goodfellow. 2018 · 2018
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A Dual Approach to Scalable Verification of Deep Networks
Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy Mann, and Pushmeet Kohli. 2018 · 2018
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Adversarial Examples that Fool both Human and Computer Vision
Gamaleldin F Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alex Kurakin, Ian Goodfellow, and Jascha Sohl-Dickstein. 2018 · 2018
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Harini Kannan, Alexey Kurakin, and Ian Goodfellow. 2018 · 2018
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Top Billing: Meet the Docs who Charge Medicare Top Dollar for Office Visits — ProPublica
Charles Ornstein and Ryann Grochowski-Jones. 2018 · 2018
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Irene Papanicolas, Liana R Woskie, and Ashish K Jha. 2018 · 2018
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Generalizability vs. Robustness: Adversarial Examples for Medical Imaging
Magdalini Paschali, Sailesh Conjeti, Fernando Navarro, and Nassir Navab. 2018 · 2018
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Certified defenses against adversarial examples
Aditi Raghunathan, Jacob Steinhardt, and Percy Liang. 2018 · 2018
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Robustness may be at odds with accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry. 2018 · 2018
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