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Artificial neural networks typically have a fixed, non-linear activation function at each neuron.
Multilayer feedforward networks are universal approximators
Hornik, Kurt, Stinchcombe, Maxwell, and White, Halbert · 1989
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Yao, Xin · 1999
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Jarrett, Kevin, Kavukcuoglu, Koray, Ranzato, M, and LeCun, Yann · 2009
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Asymptotic formulae for likelihood-based tests of new physics
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Di Lena, P., Nagata, K., and Baldi, P · 2012
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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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Snoek, Jasper, Larochelle, Hugo, and Adams, Ryan P · 2012
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Hannun, Awni Y., Case, Carl, Casper, Jared, Catanzaro, Bryan C., Diamos, Greg, Elsen, Erich, Prenger, Ryan, Satheesh, Sanjeev, Sengupta, Shubho, Coates, Adam, and Ng, Andrew Y · 2014
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Dropout: A simple way to prevent neural networks from overfitting
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