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    • GAN-based Generation and Automatic Selection of Explanations for Neural Networks 

      MISHRA, S; STOLLER, D; BENETOS, E; STURM, B; DIXON, S; SafeML ICLR 2019 Workshop (2019-05-06)
      One way to interpret trained deep neural networks (DNNs) is by inspecting characteristics that neurons in the model respond to, such as by iteratively optimising the model input (e.g., an image) to maximally activate ...