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Since the introduction of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), the literature on generative modelling has witnessed an overwhelming resurgence.
Polar factorization and monotone rearrangement of vector-valued functions
Yann Brenier · 1991
Earlier work this paper cites.
Integral probability metrics and their generating classes of functions
Alfred Müller · 1997
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Ito-langevin equations within generalized thermostatistics
Lisa Borland · 1998
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Rademacher and gaussian complexities: Risk bounds and structural results
Peter L Bartlett and Shahar Mendelson · 2002
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Optimal transport: old and new , volume 338
Cédric Villani · 2008
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Estimating divergence functionals and the likelihood ratio by convex risk minimization
XuanLong Nguyen, Martin J Wainwright, and Michael I Jordan · 2010
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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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
Earlier work this paper cites.
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2015
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Information geometry and its applications
Shun-ichi Amari · 2016
Earlier work this paper cites.
Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, and Aaron Courville · 2016
Earlier work this paper cites.
Nips 2016 tutorial: Generative adversarial networks
Ian Goodfellow · 2016
Cited alongside, same era.
beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2016
Cited alongside, same era.
Elbo surgery: yet another way to carve up the variational evidence lower bound
Matthew D Hoffman and Matthew J Johnson · 2016
Cited alongside, same era.
Learning in implicit generative models
Shakir Mohamed and Balaji Lakshminarayanan · 2016
Cited alongside, same era.
f-gan: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
Cited alongside, same era.
On the discrimination-generalization tradeoff in gans
Pengchuan Zhang, Qiang Liu, Dengyong Zhou, Tao Xu, and Xiaodong He · 2017
Later among the works it cites.
Infovae: Information maximizing variational autoencoders
Shengjia Zhao, Jiaming Song, and Stefano Ermon · 2017
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Pairwise augmented gans with adversarial reconstruction loss
Aibek Alanov, Max Kochurov, Daniil Yashkov, and Dmitry Vetrov · 2018
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Fixing a broken elbo
Alexander Alemi, Ben Poole, Ian Fischer, Joshua Dillon, Rif A Saurous, and Kevin Murphy · 2018
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A convex duality framework for gans
Farzan Farnia and David Tse · 2018
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On unifying deep generative models
Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, and Eric P Xing · 2017
Cited alongside, same era.
Approximation and convergence properties of generative adversarial learning
Shuang Liu, Olivier Bousquet, and Kamalika Chaudhuri · 2017
Cited alongside, same era.
Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2017
Cited alongside, same era.
f-gans in an information geometric nutshell
Richard Nock, Zac Cranko, Aditya K Menon, Lizhen Qu, and Robert C Williamson · 2017
Cited alongside, same era.
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, and Bernhard Schoelkopf · 2017
Cited alongside, same era.
Jonathan Weed and Francis Bach · 2017
Cited alongside, same era.
A geometric view of optimal transportation and generative model
Na Lei, Kehua Su, Li Cui, Shing-Tung Yau, and Xianfeng David Gu · 2018
Later among the works it cites.
On the implicit assumptions of gans
Ke Li and Jitendra Malik · 2018
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The inductive bias of restricted f-gans
Shuang Liu and Kamalika Chaudhuri · 2018
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Giorgio Patrini, Marcello Carioni, Patrick Forre, Samarth Bhargav, Max Welling, Rianne van den Berg, Tim Genewein, and Frank Nielsen · 2018
Later among the works it cites.
Understanding the effectiveness of lipschitz-continuity in generative adversarial nets
Zhiming Zhou, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Zhihua Zhang, and Yong Yu · 2018
Later among the works it cites.
A geometric view of optimal transportation and generative model
Na Lei, Kehua Su, Li Cui, Shing-Tung Yau, and Xianfeng David Gu · 2019
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