Deep Learning, Artificial Intelligence, Convolutional Network, Generative Adversarial, Gan.
generate samples as real as possible by setting c=b. For example, by using the 0-1 binary coding scheme: In the paper, the latter one is used. 3. Experimental Results 3.1. LSUN Dataset DCGAN Model architecture. (a): The generator. (b): The discriminator. DCGAN is used as baseline. Least square loss