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Generative adversarial networks (GANs) have achieved rapid progress in learning rich data distributions.
Maximum likelihood from incomplete data via the em algorithm
Arthur P Dempster, Nan M Laird, and Donald B Rubin · 1977
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Face recognition using eigenfaces
Matthew Turk and Alex Pentland · 1991
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On convergence properties of the em algorithm for gaussian mixtures
Lei Xu and Michael I Jordan · 1996
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Real-time american sign language recognition from video using hidden markov models
Thad Starner and Alex Pentland · 1997
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Independent component analysis: algorithms and applications
Aapo Hyvärinen and Erkki Oja · 2000
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Deep boltzmann machines
Ruslan Salakhutdinov and Geoffrey Hinton · 2009
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Generating more realistic images using gated mrf’s
Marc’aurelio Ranzato, Volodymyr Mnih, and Geoffrey E Hinton · 2010
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Invertible conditional gans for image editing
Guim Perarnau, Joost Van De Weijer, Bogdan Raducanu, and Jose M Álvarez · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Improving generative adversarial networks with denoising feature matching
David Warde-Farley and Yoshua Bengio · 2016
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Cvae-gan: fine-grained image generation through asymmetric training
Jianmin Bao, Dong Chen, Fang Wen, Houqiang Li, and Gang Hua · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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On gans and gmms
Eitan Richardson and Yair Weiss · 2018
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High-resolution image synthesis and semantic manipulation with conditional gans
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, and Bryan Catanzaro · 2018
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Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2018
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Multi-marginal wasserstein gan
Jiezhang Cao, Langyuan Mo, Yifan Zhang, Kui Jia, Chunhua Shen, and Mingkui Tan · 2019
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Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2017
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Veegan: Reducing mode collapse in gans using implicit variational learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U Gutmann, and Charles Sutton · 2017
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Lr-gan: Layered recursive generative adversarial networks for image generation
Jianwei Yang, Anitha Kannan, Dhruv Batra, and Devi Parikh · 2017
Cited alongside, same era.
Banach wasserstein gan
Jonas Adler and Sebastian Lunz · 2018
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Jinhao Dong and Tong Lin · 2019
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Mask-guided portrait editing with conditional gans
Shuyang Gu, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen, and Lu Yuan · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Mode seeking generative adversarial networks for diverse image synthesis
Qi Mao, Hsin-Ying Lee, Hung-Yu Tseng, Siwei Ma, and Ming-Hsuan Yang · 2019
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Quality aware generative adversarial networks
KANCHARLA PARIMALA and Sumohana Channappayya · 2019
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Quality aware generative adversarial networks
KANCHARLA PARIMALA and Sumohana Channappayya · 2019
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Virtual adversarial lipschitz regularization
Dávid Terjék · 2019
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Lipschitz generative adversarial nets
Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, and Zhihua Zhang · 2019
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