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Discrete flow-based models are a recently proposed class of generative models that learn invertible transformations for discrete random variables.
Practical lossless compression with latent variables using bits back coding
Townsend, J., Bird, T., and Barber, D · 1901
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Hilloc: Lossless image compression with hierarchical latent variable models
Townsend, J., Bird, T., Kunze, J., and Barber, D · 1912
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Keeping the neural networks simple by minimizing the description length of the weights
Hinton, G. E. and Van Camp, D · 1993
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2013
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Variational inference with normalizing flows
Rezende, D. J. and Mohamed, S · 2015
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The cityscapes dataset for semantic urban scene understanding
Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., and Schiele, B · 2016
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Density estimation using real nvp
Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2016
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Categorical reparameterization with gumbel-softmax
Jang, E., Gu, S., and Poole, B · 2016
Cited alongside, same era.
Conditional image generation with pixelcnn decoders
Oord, A. v. d., Kalchbrenner, N., Vinyals, O., Espeholt, L., Graves, A., and Kavukcuoglu, K · 2016
Cited alongside, same era.
Densely connected convolutional networks
Huang, G., Liu, Z., Van Der Maaten, L., and Weinberger, K. Q · 2017
Cited alongside, same era.
Glow: Generative flow with invertible 1x1 convolutions
Kingma, D. P. and Dhariwal, P · 2018
Cited alongside, same era.
Compression with flows via local bits-back coding
Ho, J., Lohn, E., and Abbeel, P · 2019
Cited alongside, same era.
Bit-swap: Recursive bits-back coding for lossless compression with hierarchical latent variables
Kingma, F., Abbeel, P., and Ho, J · 2019
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Practical full resolution learned lossless image compression
Mentzer, F., Agustsson, E., Tschannen, M., Timofte, R., and Gool, L. V · 2019
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Discrete flows: Invertible generative models of discrete data
Tran, D., Vafa, K., Agrawal, K., Dinh, L., and Poole, B · 2019
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General invertible transformations for flow-based generative modeling
Tomczak, J. M · 2020
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Discrete tree flows via tree-structured permutations
Elkady, M., Lim, J., and Inouye, D. I · 2021
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Integer discrete flows and lossless compression
Hoogeboom, E., Peters, J., van den Berg, R., and Welling, M · 2019
Cited alongside, same era.
Hoogeboom, E., Nielsen, D., Jaini, P., Forré, P., and Welling, M · 2021
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