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Convolution layers are understood to encode an infinitely strong prior on spatial locality. (Ian Goodfellow’s Deep Learning book, summary here https://medium.com/inveterate-learner/deep-learning-book-chapter-9-convolutional-networks-45e43bfc718d). From my understanding, this means that conv kernels are good at capturing regional patterns (e.g. a point here, a stroke there, etc).
Do strided transpose convolutions encode a prior of some kind as well? (an uneducated guess from my end – a preference for texture and pattern at a larger scale?)
submitted by /u/toadsofbattle
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