Comment by gwern

Highly misleading descriptions in some cases. The most recent one on embedding, the advances are real... they just come from deeper better NNs, not the fancy loss functions. Embarrassing for the researchers, yet, calling them 'not real' is false. And while http://papers.nips.cc/paper/7350-are-gans-created-equal-a-la... was interesting, it's extremely obsolete: the most recent NN considered is WGAN and the hardest dataset is CIFAR-10; that DCGAN can - with enough sheer brute force and retrying enough times - sometimes match WGAN on 28px (Fashion-MNIST) or 32px (CIFAR-10) images is mildly interesting, but pretty much irrelevant now, as stability is very important and no one in their right mind would claim that DCGAN could, say, outperform StyleGAN 2 on 1024px FFHQ or BigGAN on 512px ImageNet if only you tried DCGAN hard enough.