Training Products of Experts by Minimizing Contrastive Divergence von Hinton, Geoffrey E.

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Deep, Narrow Sigmoid Belief Networks Are Universal Approximators von Sutskever, Ilya, Hinton, Geoffrey E.

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Variational Learning for Switching State-Space Models von Ghahramani, Zoubin, Hinton, Geoffrey E.

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Energy-Based Models for Sparse Overcomplete Representations von Teh, Yee Whye, Welling, Max, Hinton, Geoffrey E

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SMEM Algorithm for Mixture Models von Ueda, Naonori, Nakano, Ryohei, Ghahramani, Zoubin, Hinton, Geoffrey E.

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The Helmholtz Machine von Dayan, Peter, Hinton, Geoffrey E., Neal, Radford M., Zemel, Richard S.

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The "Wake-Sleep" Algorithm for Unsupervised Neural Networks von Hinton, Geoffrey E., Dayan, Peter, Frey, Brendan J., Neal, Radford M.

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Using Expectation-Maximization for Reinforcement Learning von Dayan, Peter, Hinton, Geoffrey E.

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Learning distributed representations of concepts using linear relational embedding von Paccanaro, A., Hinton, G.E.

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Generative models for discovering sparse distributed representations von Hinton, Geoffrey E., Ghahramani, Zoubin

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Recognizing handwritten digits using hierarchical products of experts von Mayraz, G., Hinton, G.E.

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Self-organizing neural network that discovers surfaces in random-dot stereograms von Becker, Suzanna, Hinton, Geoffrey E

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Connectionist learning procedures von Hinton, Geoffrey E.

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Lesioning an Attractor Network: Investigations of Acquired Dyslexia von Hinton, Geoffrey E, Shallice, Tim

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Simplifying Neural Networks by Soft Weight-Sharing von Nowlan, Steven J., Hinton, Geoffrey E.

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Using generative models for handwritten digit recognition von Revow, M., Williams, C.K.I., Hinton, G.E.

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A New Learning Algorithm for Mean Field Boltzmann Machines von Welling, Max, Hinton, Geoffrey E.

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A Comparison of Classification Methods for Longitudinal fMRI Studies von Schmah, T, Yourganov, G, Zemel, RS, Hinton, GE, Small, SL, Strother, S

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Variational Learning in Nonlinear Gaussian Belief Networks von Frey, Brendan J., Hinton, Geoffrey E.

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Learning representations by back-propagating errors von Rumelhart, David E, Hinton, Geoffrey E, Williams, Ronald J

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