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Probability density estimation is a classical and well studied problem, but standard density estimation methods have historically lacked the power to model complex and high-dimensional image distributions.
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Bandwidth selection for kernel density estimation: a review of fully automatic selectors
N.-B. Heidenreich, A. Schindler, and S. Sperlich · 2013
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D. P. Kingma and M. Welling · 2013
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Generative adversarial nets
J. Donahue, P. Krähenbühl, and T. Darrell · 2016
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Image classification using naïve bayes classifier
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Flow-gan: Bridging implicit and prescribed learning in generative models
A. Grover, M. Dhar, and S. Ermon · 2017
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Masked autoregressive flow for density estimation
G. Papamakarios, I. Murray, and T. Pavlakou · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
H. Zhang, T. Xu, H. Li, S. Zhang, X. Huang, X. Wang, and D. Metaxas · 2017
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Entropic gans meet vaes: A statistical approach to compute sample likelihoods in gans
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Improved generative models for continuous image features through tree-structured non-parametric distributions
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