We propose organisation conditions that yield a method for training SOM with adaptative neighborhood radius in a variational Bayesian framework. This method is validated on a non-stationary setting and compared in an high-dimensional setting with an other adaptative method.
Cite
@article{arxiv.2208.11337,
title = {A Bayesian Variational principle for dynamic Self Organizing Maps},
author = {Anthony Fillion and Thibaut Kulak and François Blayo},
journal= {arXiv preprint arXiv:2208.11337},
year = {2022}
}