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Merge pull request #900 from tensorflow/npapernot-v3
prepare readme for v3 release
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README.md

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# CleverHans (latest release: v2.1.0)
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# CleverHans (latest release: v3.0.0)
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<img src="https://github.com/tensorflow/cleverhans/blob/master/assets/logo.png?raw=true" alt="cleverhans logo">
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## Tutorials: `cleverhans_tutorials` directory
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To help you get started with the functionalities provided by this library, the
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`cleverhans_tutorials/' folder comes with the following tutorials:
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`cleverhans_tutorials/` folder comes with the following tutorials:
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* **MNIST with FGSM** ([code](cleverhans_tutorials/mnist_tutorial_tf.py)): this
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tutorial covers how to train a MNIST model using TensorFlow,
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craft adversarial examples using the [fast gradient sign method](https://arxiv.org/abs/1412.6572),
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* Report any configuration variables used to determine the behavior of the attack.
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For example, you might report "We benchmarked the robustness of our method to
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adversarial attack using v2.1.0 of CleverHans. On a test set modified by the
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adversarial attack using v3.0.0 of CleverHans. On a test set modified by the
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`FastGradientMethod` with a max-norm `eps` of 0.3, we obtained a test set accuracy of 71.3%."
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## Citing this work
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## Authors
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This library is managed and maintained by Ian Goodfellow (Google Brain),
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Nicolas Papernot (Pennsylvania State University), and
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Ryan Sheatsley (Pennsylvania State University).
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This library is managed and maintained by Ian Goodfellow (Google Brain) and
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Nicolas Papernot (Google Brain).
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The following authors contributed 100 lines or more (ordered according to the GitHub contributors page):
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* Nicolas Papernot (Pennsylvania State University, Google Brain intern)
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* Fartash Faghri (University of Toronto, Google Brain intern)
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* Nicholas Carlini (UC Berkeley)
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* Ian Goodfellow (Google Brain)
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* Reuben Feinman (Symantec)
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* Nicolas Papernot (Google Brain)
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* Nicholas Carlini (Google Brain)
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* Fartash Faghri (University of Toronto)
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* Tzu-Wei Sung (National Taiwan University)
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* Alexey Kurakin (Google Brain)
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* Reuben Feinman (New York University)
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* Phani Krishna (Video Analytics Lab)
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* David Berthelot (Google Brain)
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* Tom Brown (Google Brain)
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* Cihang Xie (Johns Hopkins)
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* Yash Sharma (The Cooper Union)
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* Tom Brown (Google Brain)
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* Aashish Kumar
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* Aurko Roy (Google Brain)
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* Alexander Matyasko (Nanyang Technological University)
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* Anshuman Suri (Microsoft)
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* Yen-Chen Lin (MIT)
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* Vahid Behzadan (Kansas State)
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* Karen Hambardzumyan (YerevaNN)
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* Jonathan Uesato (DeepMind)
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* Zhishuai Zhang (Johns Hopkins)
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* Yi-Lin Juang (NTUEE)
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* Karen Hambardzumyan (YerevaNN)
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* Catherine Olsson (Google Brain)
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* Aidan Gomez (University of Oxford)
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* Zhi Li (University of Toronto)
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* Ryan Sheatsley (Pennsylvania State University)
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* Yi-Lin Juang (NTUEE)
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* Pratyush Sahay
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* Abhibhav Garg (IIT Delhi)
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* Jonathan Uesato (MIT)
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* Willi Gierke (Hasso Plattner Institute)
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* Aditi Raghunathan (Stanford University)
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* Yang Song (Stanford University)
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* Riccardo Volpi (Italian Institute of Technology)
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* Angus Galloway (University of Guelph)
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* Yinpeng Dong (Tsinghua University)
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* David Berthelot (Google Brain)
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* Paul Hendricks (NVIDIA)
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* Willi Gierke (Hasso Plattner Institute)
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* Bruno López
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* Jonas Rauber (IMPRS)
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* Paul Hendricks (NVIDIA)
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* Ryan Sheatsley (Pennsylvania State University)
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* Rujun Long (0101.AI)
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* Bogdan Kulynych (EPFL)
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* Erfan Noury (UMBC)
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* Robert Wagner (Case Western Reserve University)
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## Copyright
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