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Ryan Lagerquist, Amy McGovern, Cameron R. Homeyer, David John Gagne II, and Travis Smith

except the last follow this linear transformation with leaky ReLU and batch normalization, like the convolutional layers. The last dense layer uses the sigmoid activation function (section 6.2.2.2 of Goodfellow et al. 2016 ), which forces the output to range over [0, 1], allowing it to be interpreted as a probability. The last dense layer does not use batch normalization, because this would force the outputs to a Gaussian distribution, which permits values outside [0, 1] and is therefore invalid for

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