[R] AdaGAN: Boosting Generative Models, Iliya Tolstikhin (NIPS2017 paper) • r/MachineLearning

Do we really need to have extensive results on MNIST, CIFAR, Imagenet, Celeba, ... to claim that a paper is convincing? This paper addresses a very specific issue of generative models, which is the fact that they mostly fail to demonstrate the same diversity as the original data. Their theoretical claims are clear, and to the best of my understanding, grounded. Their synthetic experiment pinpoints the variability problem of GANs, and demonstrate the superiority of their approach in this particular setup. What would an experiment on Imagenet add to their point?