2016 was a vintage year for GAN litterature, with the technique gaining traction and many theoretical breakthroughs on top of much increased quality ( see the recent PPGN paper for impressive results on ImageNet).
Deep Convolutional GANs, A. Radford, 2015
Auxiliary Classifier GANs, A. Odena, 2016
Improved Techniques for training GANs, T. Salimans, 2016
Energy-Based GANs, J. Zhao, 2016
Adversarially Learned Inference, V. Dumoulin, 2016
Wasserstein GANs, M. Arjovsky, 2017 (+ Towards Principled Methods for training GANs, M. Arjovsky, 2016 / Improved Training of Wasserstein GANs, I. Gulrajani, 2017)