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Latent Variable Modelling with <span>G</span>aussian Processes

at Workshop on Probabilistic formulation of the inverse problem and application to image reconstruction, Neuroscience Research Institute, University of Manchester, U.K. on Sep 13, 2007 [pdf]
Neil D. Lawrence, University of Manchester

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Abstract

In this talk we will briefly describe the Gaussian process latent variable model, an approach to probabilistic modelling of data through non-linear dimensional reduction. The model takes a dual approach to statistical inference and can be shown to generalise PCA. We will briefly introduce the model and quickly show some example applications.