By Topic

Self-Organizing Maps as Traveling Computational Templates

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Knuuttila, T. ; Helsinki Univ., Helsinki ; Rusanen, A.-M. ; Honkela, T.

In this article we approach neural networks as computational templates that travel across various sciences. Traditionally, it has been thought that models are primarily models of some target systems: they are assumed to represent partially or completely their target systems. We argue, instead, that many computational models cannot easily be conceived of in representational terms. Rather, they can be seen as models for various epistemic endeavors. Apart from dealing with the question of representation, we discuss also what implications the genuinely cross-disciplinary computational templates such as neural networks have for the organization of science. We use Self-organizing maps as an example through which we study the aforementioned questions.

Published in:

Neural Networks, 2007. IJCNN 2007. International Joint Conference on

Date of Conference:

12-17 Aug. 2007