Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. Generative Adversarial Networks.

Alec Radford, Luke Metz, Soumith Chintala. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.

Junbo Zhao, Michael Mathieu, Yann LeCun. Energy-based Generative Adversarial Network. (slides: https://drive.google.com/file/d/0BxKBnD5y2M8NbzBUbXRwUDBZOVU/view)

Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen. Improved Techniques for Training GANs.

David Pfau, Oriol Vinyals. Connecting Generative Adversarial Networks and Actor-Critic Methods.

Chelsea Finn, Paul Christiano, Pieter Abbeel, Sergey Levine. A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models.

Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets.

Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu. Conditional Image Generation with PixelCNN Decoders.

Mehdi Mirza, Simon Osindero. Conditional Generative Adversarial Nets.

Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, Brendan Frey. Adversarial AutoEncoders.

Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee. Generative Adversarial Text to Image Synthesis.

Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros. Image-to-Image Translation with Conditional Adversarial Networks.

Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu. SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient.

Anh Nguyen, Jason Yosinski, Yoshua Bengio, Alexey Dosovitskiy, Jeff Clune. Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space.

Nir Baram, Oron Anschel, Shie Mannor. Model-based Adversarial Imitation Learning.

Emily Denton, Sam Gross, Rob Fergus. Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks.

NIPS 2017 Workshop. https://sites.google.com/site/nips2016adversarial/

Ian Goodfellow. Introduction to Generative Adversarial Networks. http://www.iangoodfellow.com/slides/2016-12-9-gans.pdf Soumith Chintala.

Sebastian Nowozin, Botond Cseke, Ryota Tomioka. f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. (slides http://www.nowozin.net/sebastian/blog/nips-2016-generative-adversarial-training-workshop-talk.html).

[1] Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. NIPS, 2015. [2] Jeff Donahue, Philipp Krähenbühl, Trevor Darrell. Adversarial Feature Learning. arXiv, 2016. [3] Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martin Arjovsky, Olivier Mastropietro, Aaron Courville. Adversarially Learned Inference. arXiv, 2016. [4] Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani. Training generative neural networks via Maximum Mean Discrepancy optimization. arXiv, 2015. [5] Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. Generative Adversarial Networks. NIPS, 2014. [6] Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy. Explaining and Harnessing Adversarial Examples. ICLR, 2015. [7] Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander Smola. A Kernel Two-Sample Test. JMLR, 2012. [8] Diederik P Kingma, Max Welling. Auto-Encoding Variational Bayes. ICLR, 2014. [9] Yujia Li, Kevin Swersky, Richard Zemel. Generative Moment Matching Networks. arXiv, 2015. [10] Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, Brendan Frey. Adversarial Autoencoders. ICLR, 2016. [11] Michael Mathieu, Camille Couprie, Yann LeCun. Deep multi-scale video prediction beyond mean square error. ICLR, 2016. [12] Mehdi Mirza, Simon Osindero. Conditional Generative Adversarial Nets. arXiv, 2014. [13] Sebastian Nowozin, Botond Cseke, Ryota Tomioka. f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. arXiv, 2016. [14] Alec Radford, Luke Metz, Soumith Chintala. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. ICLR, 2016. [15] Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee. Generative Adversarial Text to Image Synthesis. ICML, 2016. [16] Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen. Improved Techniques for Training GANs. arXiv, 2016.