Foolbox: A Python toolbox to benchmark the robustness of machine learning models

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Intriguing properties of neural networks
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Szegedy, Christian, Zaremba, Wojciech, Sutskever, Ilya, Bruna, Joan, Erhan, Dumitru, Goodfellow, Ian J., and Fergus, Rob · 2013
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Original
Goodfellow, Ian J, Shlens, Jonathon, and Szegedy, Christian · 2014
Earlier work this paper cites.
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
Original
Chen, Tianqi, Li, Mu, Li, Yutian, Lin, Min, Wang, Naiyan, Wang, Minjie, Xiao, Tianjun, Xu, Bing, Zhang, Chiyuan, and Zhang, Zheng · 2015
Earlier work this paper cites.
Lasagne: First release., August 2015
Dieleman, Sander, Schlüter, Jan, Raffel, Colin, Olson, Eben, Sonderby, Søren Kaae, et al · 2015
Earlier work this paper cites.

Deepfool: a simple and accurate method to fool deep neural networks
Original
Moosavi-Dezfooli, Seyed-Mohsen, Fawzi, Alhussein, and Frossard, Pascal · 2015
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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Abadi, Martín, Agarwal, Ashish, Barham, Paul, et al · 2016
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Theano: A python framework for fast computation of mathematical expressions
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Al-Rfou, Rami, Alain, Guillaume, Almahairi, Amjad, Angermüller, Christof, et al · 2016
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Simple black-box adversarial perturbations for deep networks
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Narodytska, Nina and Kasiviswanathan, Shiva Prasad · 2016
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cleverhans v1.0.0: an adversarial machine learning library
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Papernot, Nicolas, Goodfellow, Ian, Sheatsley, Ryan, Feinman, Reuben, and McDaniel, Patrick
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Practical black-box attacks against deep learning systems using adversarial examples
Original
Papernot, Nicolas, McDaniel, Patrick D., Goodfellow, Ian J., Jha, Somesh, Celik, Z. Berkay, and Swami, Ananthram
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The limitations of deep learning in adversarial settings
Papernot, N., McDaniel, P., Jha, S., Fredrikson, M., Celik, Z. B., and Swami, A · 2016
Later among the works it cites.
Comment on “Biologically inspired protection of deep networks from adversarial attacks”
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Brendel, W. and Bethge, M · 2017
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Decision-based adversarial attacks: Reliable attacks against black-box machine learning models
Brendel, Wieland, Rauber, Jonas, and Bethge, Matthias · 2018
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