Abstract
We create a new form of topographic map which is based on a nonlinear mapping of a space of latent points. The mapping of these latent points into data space creates centres which are equivalent to those of the standard SOM. We relate this mapping to the Generative Topographic Mapping, GTM. We then show that it is rather simple and computationally inexpensive to grow one of these maps and that a probabilistic interpretation of these maps facilitates our investigation of alternative algorithms.
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© 2005 Springer-Verlag Berlin Heidelberg
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Fyfe, C. (2005). The Topographic Product of Experts. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_62
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DOI: https://doi.org/10.1007/11550822_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28752-0
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