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Flow-based generative models (Dinh et al., 2014) are conceptually attractive due to tractability of the exact log-likelihood, tractability of exact latent-variable inference, and parallelizability of both training and synthesis.
Higher order statistical decorrelation without information loss
Deco, G. and Brauer, W. (1995) · 1995
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Long Short-Term Memory
Hochreiter, S. and Schmidhuber, J. (1997) · 1997
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Learning multiple layers of features from tiny images
Krizhevsky, A. (2009) · 2009
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Generating sequences with recurrent neural networks
Graves, A. (2013) · 2013
Earlier work this paper cites.
Auto-encoding variational Bayes
Kingma, D. P. and Welling, M. (2013) · 2013
Earlier work this paper cites.
Nice: non-linear independent components estimation
Dinh, L., Krueger, D., and Bengio, Y. (2014) · 2014
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014) · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S. and Szegedy, C. (2015) · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. and Ba, J. (2015) · 2015
Earlier work this paper cites.
Variational inference with normalizing flows
Rezende, D. and Mohamed, S. (2015) · 2015
Cited alongside, same era.
Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · 2015
Cited alongside, same era.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Yu, F., Zhang, Y., Song, S., Seff, A., and Xiao, J. (2015) · 2015
Cited alongside, same era.
Density estimation using Real NVP
Dinh, L., Sohl-Dickstein, J., and Bengio, S. (2016) · 2016
Cited alongside, same era.
Identity mappings in deep residual networks
He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
Cited alongside, same era.
The reversible residual network: Backpropagation without storing activations
Gomez, A. N., Ren, M., Urtasun, R., and Grosse, R. B. (2017) · 2017
Later among the works it cites.
Progressive growing of gans for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J. (2017) · 2017
Later among the works it cites.
Parallel wavenet: Fast high-fidelity speech synthesis
Oord, A. v. d., Li, Y., Babuschkin, I., Simonyan, K., Vinyals, O., Kavukcuoglu, K., Driessche, G. v. d., Lockhart, E., Cobo, L. C., Stimberg, F., et al. (2017) · 2017
Later among the works it cites.
Masked autoregressive flow for density estimation
Papamakarios, G., Murray, I., and Pavlakou, T. (2017) · 2017
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Gradient checkpointing
Salimans, T. and Bulatov, Y. (2017) · 2017
Later among the works it cites.
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Improved variational inference with inverse autoregressive flow
Kingma, D. P., Salimans, T., Jozefowicz, R., Chen, X., Sutskever, I., and Welling, M. (2016) · 2016
Cited alongside, same era.
Pixel recurrent neural networks
Oord, A. v. d., Kalchbrenner, N., and Kavukcuoglu, K. (2016) · 2016
Cited alongside, same era.
Weight normalization: A simple reparameterization to accelerate training of deep neural networks
Salimans, T. and Kingma, D. P. (2016) · 2016
Cited alongside, same era.
Wavenet: A generative model for raw audio
Van Den Oord, A., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., and Kavukcuoglu, K. (2016) · 2016
Cited alongside, same era.
Pixel recurrent neural networks
van den Oord, A., Kalchbrenner, N., and Kavukcuoglu, K. (2016a)
Cited in the paper.
Conditional image generation with PixelCNN decoders
van den Oord, A., Kalchbrenner, N., Vinyals, O., Espeholt, L., Graves, A., and Kavukcuoglu, K. (2016b)
Cited in the paper.
Flow-gan: Combining maximum likelihood and adversarial learning in generative models
Grover, A., Dhar, M., and Ermon, S. (2018) · 2018
Closest in time.
Variational autoencoders
Kingma, D. P. and Welling, M. (2018) · 2018
Closest in time.
Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, Ł., Shazeer, N., and Ku, A. (2018) · 2018
Closest in time.