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We consider the problem of lossy image compression with deep latent variable models.
Practical lossless compression with latent variables using bits back coding
James Townsend, Tom Bird, and David Barber · 1901
Earlier work this paper cites.
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James Townsend, Thomas Bird, Julius Kunze, and David Barber · 1912
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Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Salvator Lombardo, Jun Han, Christopher Schroers, and Stephan Mandt · 2019
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