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Efficient Adversarial Input Generation via Neural Net Patching
Thus, this paper presents a novel way to generate input perturbations that are adversarial for a given network by using an efficient network patching technique.
Efficiently Finding Adversarial Examples with DNN Preprocessing
Deep Neural Networks (DNNs) are everywhere, frequently performing a fairly complex task that used to be unimaginable for machines to carry out.
Permutation Invariance of Deep Neural Networks with ReLUs
Consider a deep neural network (DNN) that is being used to suggest the direction in which an aircraft must turn to avoid a possible collision with an intruder aircraft.
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