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link to the paper.


Their method more maximizing the cross entropy yields very peculiar results if you look at the images as the hyper-parameter iterations go up. It seems as if what we are seeing is some convolution with some peculiar form of noise. I wonder what the structure across these adversarial images looks like and whether it could provide some insight into certain patterns in cov net learning?

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