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Stochastic binary hidden units in a multi-layer perceptron (MLP) network give at least three potential benefits when compared to deterministic MLP networks.
Learning stochastic feedforward networks
Neal, Radford M · 1990
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Creating artificial neural networks that generalize
Sietsma, Jocelyn and Dow, Robert JF · 1991
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Connectionist learning of belief networks
Neal, Radford M · 1992
Earlier work this paper cites.
Mean field theory for sigmoid belief networks
Saul, Lawrence K, Jaakkola, Tommi, and Jordan, Michael I · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Léon, Bengio, Yoshua, and Haffner, Patrick · 1998
Earlier work this paper cites.
The optimal reward baseline for gradient-based reinforcement learning
Weaver, Lex and Tao, Nigel · 2001
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Pattern recognition and machine learning , volume 1
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Theano: a CPU and GPU math expression compiler
Bergstra, James, Breuleux, Olivier, Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Desjardins, Guillaume, Turian, Joseph, Warde-Farley, David, and Bengio, Yoshua · 2010
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The Toronto face database
Susskind, Joshua, Anderson, Adam, and Hinton, Geoffrey · 2010
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Theano: new features and speed improvements
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Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E, Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
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Estimating or propagating gradients through stochastic neurons for conditional computation
Bengio, Yoshua, Léonard, Nicholas, and Courville, Aaron · 2013
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Cognitive computing systems: Algorithms and applications for networks of neurosynaptic cores
Esser, Steve K, Andreopoulos, Alexander, Appuswamy, Rathinakumar, Datta, Pallab, Barch, Davis, Amir, Arnon, Arthur, John, Cassidy, Andrew, Flickner, Myron, Merolla, Paul, et al · 2013
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Auto-encoding variational Bayes
Kingma, Diederik P and Welling, Max · 2013
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Learning stochastic feedforward neural networks
Tang, Yichuan and Salakhutdinov, Ruslan · 2013
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Neural variational inference and learning in belief networks
Mnih, Andriy and Gregor, Karol · 2014
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Raiko, Tapani, Valpola, Harri, and LeCun, Yann · 2012
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Stochastic back-propagation and variational inference in deep latent Gaussian models
Rezende, Danilo Jimenez, Mohamed, Shakir, and Wierstra, Daan · 2014
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