Unsupervised Variational Bayesian Learning of Nonlinear Models

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In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is handled by linearizing it using a Gauss

Antti Honkela, Harri Valpola

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2004
Where	NIPS
Authors	Antti Honkela, Harri Valpola

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Unsupervised Variational Bayesian Learning of Nonlinear Models

Factor Analysis | NIPS 2004 | NIPS 2007 | Nonlinear Factor Analysis | Nonlinear Generative Models |

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