Abstract. The generative topographic mapping (GTM) has been proposed as a statistical model to represent high dimensional data by means of a sparse lattice of points in latent spac...
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
The elastic net and related algorithms, such as generative topographic mapping, are key methods for discretized dimension-reduction problems. At their heart are priors that specify...
We consider two layered binary state neural networks in which cellular topographic self-organization occurs under correlational learning. The main result is that for separable inpu...