Unsupervised Variational Bayesian Learning of Nonlinear Models

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

• Type: Conference
• Year: 2004
• Where: NIPS
• Authors: Antti Honkela, Harri Valpola
• Keywords: Factor Analysis, NIPS 2004, NIPS 2007, Nonlinear Factor Analysis, Nonlinear Generative Models