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Reparameterization of variational auto-encoders with continuous random variables is an effective method for reducing the variance of their gradient estimates.
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Diederik P Kingma and Max Welling · 2013
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Diederik P Kingma and Max Welling · 2013
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SM Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Geoffrey E Hinton, et al · 2016
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The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison, Andriy Mnih, and Yee Whye Teh · 2017
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Sticking the landing: Simple, lower-variance gradient estimators for variational inference
Geoffrey Roeder, Yuhuai Wu, and David K Duvenaud · 2017
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George Tucker, Andriy Mnih, Chris J Maddison, John Lawson, and Jascha Sohl-Dickstein · 2017
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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017
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Training Deep Neural Networks via Direct Loss Minimization
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