This set of notebooks is a companion material to my series of articles on the Starschema blog discussing competitive neural networks. Unlike error-correction neural networks, to which the feedforward backpropagation neural nets you know and love belong, competitive neural networks have an entirely different idea of what neurons do, and indeed model different brain processes (associative or Hebbian learning versus the ventral stream's gradually more complex and semantic process of understanding). While these blog posts are far from giving you the complete lowdown, they're a fun introduction to the subject.
| Blog post | Companion notebook | NBViewer | |
|---|---|---|---|
| 1 | Funderstanding competitive neural networks | notebook | nbviewer |
| 2 | Self-Organising Feature Maps for fun and profit | notebook | nbviewer |
| 3 | Growing Neural Gas models: theory and practice | notebook | nbviewer |
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Prudent, Yann, and Abdellatif Ennaji. "An incremental growing neural gas learns topologies." Proceedings of the 2005 IEEE International Joint Conference on Neural Networks, Vol. 2. IEEE, 2005.
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Daszykowski, Michael, Beata Walczak, and Desire L. Massart. "On the optimal partitioning of data with k-means, growing k-means, neural gas, and growing neural gas." Journal of Chemical Information and Computer Sciences 42.6 (2002): 1378-1389.
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Holdstein, Yaron, and Anath Fischer. "Three-dimensional surface reconstruction using meshing growing neural gas (MGNG)." The Visual Computer 24.4 (2008): 295-302.
The author wishes to thank Starschema for their generous research time allowance that has made the work on these posts and notebooks possible in the first place. I'd also like to thank my wife Katie for putting up with me while I was working on this (it's been a busy few weeks)