example/adversary/README.md - mxnet - Git at Google

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 # Adversarial examples

 This demonstrates the concept of "adversarial examples" from [1] showing how to fool a well-trained CNN.
 Adversarial examples are samples where the input has been manipulated to confuse a model (i.e. confident in an incorrect prediction) but where the correct answer still appears obvious to a human.
 This method for generating adversarial examples uses the gradient of the loss with respect to the input to craft the adversarial examples.

 [1] Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." [arXiv preprint arXiv:1412.6572 (2014)](https://arxiv.org/abs/1412.6572)
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	# Adversarial examples

	This demonstrates the concept of "adversarial examples" from [1] showing how to fool a well-trained CNN.
	Adversarial examples are samples where the input has been manipulated to confuse a model (i.e. confident in an incorrect prediction) but where the correct answer still appears obvious to a human.
	This method for generating adversarial examples uses the gradient of the loss with respect to the input to craft the adversarial examples.

	[1] Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." [arXiv preprint arXiv:1412.6572 (2014)](https://arxiv.org/abs/1412.6572)