Adversarial attacks and model uncertainty

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In this project, we wanted to understand how to build uncertainty aware neural networks - for classifying an image as a cat/dog, think of this as giving a confidence interval along with a probability estimate. We started out in a theoretical setting: we looked at how dropout can be used as a bayesian approximation ( source ). The application in mind was adversarial attacks - using uncertainty…

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