i-RevNet: Deep Invertible Networks

ICLR 2018 Jörn-Henrik JacobsenArnold SmeuldersEdouard Oyallon

It is widely believed that the success of deep convolutional networks is based on progressively discarding uninformative variability about the input with respect to the problem at hand. This is supported empirically by the difficulty of recovering images from their hidden representations, in most commonly used network architectures... (read more)

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