A Bayesian Variational principle for dynamic Self Organizing Maps
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 8 references that are in the map. First posted on arXiv 24 Aug 2022.
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References · 1
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
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