Newmu/dcgan_code: Deep Convolutional Generative Adversarial Networks

Deep Convolutional Generative Adversarial Networks - Newmu/dcgan_code

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford, Luke Metz , Soumith Chintala All images in this paper are generated by a neural network. They are NOT REAL. Full paper here: http://arxiv.org/abs/1511.06434 ###Other implementations of DCGAN Torch Chainer TensorFlow ##Summary of DCGAN We stabilize Generative Adversarial networks with some architectural constraints Replace any pooling layers with strided convolutions (discriminator) and fractional-strided convolutions (generator). Use batchnorm in both the generator and the discriminator R

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