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Allowing effective inference of latent vectors while training GANs can greatly increase their applicability in various downstream tasks.
SDGM: Sparse Bayesian Classifier Based on a Discriminative Gaussian Mixture Model
Hayashi, H.; and Uchida, S. 2019 · 1911
Earlier work this paper cites.
Divergence measures based on the Shannon entropy
Lin, J. 1991 · 1991
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Netzer, Y.; Wang, T.; Coates, A.; Bissacco, A.; Wu, B.; and Ng, A. Y. 2011 · 2011
Earlier work this paper cites.
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
Goodfellow, I. J.; Bulatov, Y.; Ibarz, J.; Arnoud, S.; and Shet, V. 2013 · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Kingma, D. P.; and Welling, M. 2013 · 2013
Earlier work this paper cites.
Improving neural networks with dropout
Srivastava, N. 2013 · 2013
Earlier work this paper cites.
Generative Adversarial Networks
Goodfellow, I. J.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2017 · 2014
Earlier work this paper cites.
Deep Learning Face Attributes in the Wild
Liu, Z.; Luo, P.; Wang, X.; and Tang, X. 2015 · 2015
Earlier work this paper cites.
Adversarial autoencoders
Makhzani, A.; Shlens, J.; Jaitly, N.; and Goodfellow, I. J. 2016 · 2016
Earlier work this paper cites.
Deep multi-scale video prediction beyond mean square error
Mathieu, M.; Couprie, C.; and LeCun, Y. 2016 · 2016
Cited alongside, same era.
Towards Principled Methods for Training Generative Adversarial Networks
Arjovsky, M.; and Bottou, L. 2017 · 2017
Cited alongside, same era.
Autoencoding beyondpixels using a learned similarity metric
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Cited alongside, same era.
Adversarial feature learning
Donahue, J.; Krähenbühl, P.; and Darrell, T. 2017 · 2017
Cited alongside, same era.
Adversarial feature learning
Dumoulin, V.; Belghazi, I.; Poole, B.; Arjovsky, A. L. M.; Mas-tropietro, O.; and Courville, A. C. 2017 · 2017
Cited alongside, same era.
Triangle generative adversarial networks
Gan, Z.; Chen, L.; Wang, W.; Pu, Y.; Zhang, Y.; Liu, H.; Li, C.; and Carin, L. 2017 · 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Mescheder, L.; Nowozin, S.; and Geiger, A. 2017 · 2017
Later among the works it cites.
Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C.; Ioffe, S.; Vanhoucke, V.; and Alemi, A. A. 2017 · 2017
Later among the works it cites.
Towards Deeper Understanding of Variational Autoencoding Models
Zhao, S.; Song, J.; and Ermon, S. 2017 · 2017
Later among the works it cites.
Spectral normalization for generative adversarial networks
Miyato, T.; Kataoka, T.; Koyama, M.; and Yoshida, Y. 2018 · 2018
Later among the works it cites.
Jointgan: Multi-domain joint distribution learning with generative adversarial nets
Pu, Y.; Dai, S.; Gan, Z.; Wang, W.; Wang, G.; Zhang, Y.; Henao, R.; and Carin, L. 2018 · 2018
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Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2017 · 2017
Cited alongside, same era.
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference
Kumar, A.; Sattiger, P.; and Fletcher, T. 2017 · 2017
Cited alongside, same era.
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
Li, C.; Liu, H.; Chen, C.; Pu, Y.; Chen, L.; Henao, R.; and Carin, L. 2017a · 2017
Cited alongside, same era.
Triple Generative Adversarial Nets
Li, C.; Xu, K.; Zhu, J.; and Zhang, B. 2017b
Cited in the paper.
Later among the works it cites.
It Takes (Only) Two: Adversarial Generator-Encoder Networks
Ulyanov, D.; Vedaldi, A.; and Lempitsky, V. 2018 · 2018
Later among the works it cites.
Learning about an exponential amount of conditional distributions
Belghazi, M.; Oquab, M.; and Lopez-Paz, D. 2019 · 2019
Later among the works it cites.
Large scale adversarial representation learning
Donahue, J.; and Simonyan, K. 2019 · 2019
Later among the works it cites.