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We propose a new family of optimization criteria for variational auto-encoding models, generalizing the standard evidence lower bound.
Auto-Encoding Variational Bayes
Kingma, D. P and Welling, M · 2013
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Generative adversarial nets
Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Jimenez Rezende, D., Mohamed, S., and Wierstra, D · 2014
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Generating sentences from a continuous space
Bowman, Samuel R., Vilnis, Luke, Vinyals, Oriol, Dai, Andrew M., Józefowicz, Rafal, and Bengio, Samy · 2015
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Importance weighted autoencoders
Burda, Yuri, Grosse, Roger, and Salakhutdinov, Ruslan · 2015
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A recurrent latent variable model for sequential data
Chung, Junyoung, Kastner, Kyle, Dinh, Laurent, Goel, Kratarth, Courville, Aaron C., and Bengio, Yoshua · 2015
Earlier work this paper cites.
Autoencoding beyond pixels using a learned similarity metric
Larsen, Anders Boesen Lindbo, Sønderby, Søren Kaae, and Winther, Ole · 2015
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, Alec, Metz, Luke, and Chintala, Soumith · 2015
Cited alongside, same era.
An architecture for deep, hierarchical generative models
Bachman, Philip · 2016
Cited alongside, same era.
Learning to generate samples from noise through infusion training
Bordes, Florian, Honari, Sina, and Vincent, Pascal · 2016
Cited alongside, same era.
Chen, Xi, Kingma, Diederik P, Salimans, Tim, Duan, Yan, Dhariwal, Prafulla, Schulman, John, Sutskever, Ilya, and Abbeel, Pieter · 2016
Cited alongside, same era.
Generating images with perceptual similarity metrics based on deep networks
Dosovitskiy, Alexey and Brox, Thomas · 2016
Cited alongside, same era.
Ladder Variational Autoencoders
Kaae Sønderby, C., Raiko, T., Maaløe, L., Kaae Sønderby, S., and Winther, O · 2016
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Improving variational inference with inverse autoregressive flow
Kingma, Diederik P, Salimans, Tim, and Welling, Max · 2016
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Discriminative regularization for generative models
Lamb, Alex, Dumoulin, Vincent, and Courville, Aaron · 2016
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f-gan: Training generative neural samplers using variational divergence minimization
Nowozin, Sebastian, Cseke, Botond, and Tomioka, Ryota · 2016
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Wasserstein GAN
Arjovsky, M., Chintala, S., and Bottou, L · 2017
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Pixelvae: A latent variable model for natural images
Gulrajani, Ishaan, Kumar, Kundan, Ahmed, Faruk, Taiga, Adrien Ali, Visin, Francesco, Vázquez, David, and Courville, Aaron C · 2016
Cited alongside, same era.
Conditional image generation with pixelcnn decoders
van den Oord, Aaron, Kalchbrenner, Nal, Espeholt, Lasse, Vinyals, Oriol, Graves, Alex, et al
Cited in the paper.
Pixel recurrent neural networks
van den Oord, Aäron, Kalchbrenner, Nal, and Kavukcuoglu, Koray
Cited in the paper.
Salimans, Tim, Karpathy, Andrej, Chen, Xi, and Kingma, Diederik P · 2017
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