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The bits-back argument suggests that latent variable models can be turned into lossless compression schemes.
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Dropout: A simple way to prevent neural networks from overfitting
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R · 2014
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Nice: non-linear independent components estimation
Dinh, L., Krueger, D., and Bengio, Y · 2015
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Duda, J., Tahboub, K., Gadgil, N. J., and Delp, E. J · 2015
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Kingma, D. and Ba, J · 2015
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Towards conceptual compression
Gregor, K., Besse, F., Rezende, D. J., Danihelka, I., and Wierstra, D · 2016
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Video pixel networks
Kalchbrenner, N., Oord, A., Simonyan, K., Danihelka, I., Vinyals, O., Graves, A., and Kavukcuoglu, K · 2017
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Salimans, T., Karpathy, A., Chen, X., and Kingma, D. P · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Learning hierarchical features from deep generative models
Zhao, S., Song, J., and Ermon, S · 2017
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Pixelsnail: An improved autoregressive generative model
Chen, X., Mishra, N., Rohaninejad, M., and Abbeel, P · 2018
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Neural machine translation in linear time
Kalchbrenner, N., Espeholt, L., Simonyan, K., Oord, A. v. d., Graves, A., and Kavukcuoglu, K · 2016
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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
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Pixel recurrent neural networks
Oord, A. V., Kalchbrenner, N., and Kavukcuoglu, K · 2016
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Chen, X., Kingma, D. P., Salimans, T., Duan, Y., Dhariwal, P., Schulman, J., Sutskever, I., and Abbeel, P · 2017
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Density estimation using Real NVP
Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2017
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Weight normalization: A simple reparameterization to accelerate training of deep neural networks
Salimans, T. and Kingma, D. P
Cited in the paper.
GNU Gzip, Aug 2018
Gailly, J.-l. and Adler, M · 2018
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Efficient neural audio synthesis
Kalchbrenner, N., Elsen, E., Simonyan, K., Noury, S., Casagrande, N., Lockhart, E., Stimberg, F., Oord, A., Dieleman, S., and Kavukcuoglu, K · 2018
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Progressive growing of GANs for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Kingma, D. P. and Dhariwal, P · 2018
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Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, L., Shazeer, N., Ku, A., and Tran, D · 2018
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Practical lossless compression with latent variables using bits back coding
Townsend, J., Bird, T., and Barber, D · 2019
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