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Modeling the distribution of natural images is a landmark problem in unsupervised learning.
Connectionist learning of belief networks
Neal, Radford M · 1992
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Bengio, Yoshua and Bengio, Samy · 2000
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He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian · 2015
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Kalchbrenner, Nal, Danihelka, Ivo, and Graves, Alex · 2015
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ImageNet Large Scale Visual Recognition Challenge
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Markov chain monte carlo and variational inference: Bridging the gap
Salimans, Tim, Kingma, Diederik P, and Welling, Max · 2015
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Factoring variations in natural images with deep gaussian mixture models
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The student-t mixture as a natural image patch prior with application to image compression
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Deep unsupervised learning using nonequilibrium thermodynamics
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Parallel multi-dimensional lstm, with application to fast biomedical volumetric image segmentation
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Generative image modeling using spatial LSTMs
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A note on the evaluation of generative models
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Highway long short-term memory RNNs for distant speech recognition
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