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  4. tanh Neurons are Bayesian Decision Makers
 
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2021
Conference Paper
Title

tanh Neurons are Bayesian Decision Makers

Abstract
The hyperbolic tangent (tanh) is a traditional choice for the activation function of the neurons of an artificial neural network. Here, we go through a simple calculation that shows that this modeling choice is linked to Bayesian decision theory. Our brief, tutorial-like discussion is intended as a reference to an observation rarely mentioned in standard textbooks.
Author(s)
Bauckhage, Christian  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Sifa, Rafet  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Hecker, Dirk  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Mainwork
Intelligent Systems and Applications. Proceedings of the 2020 Intelligent Systems Conference, IntelliSys 2020. Vol.3  
Project(s)
ML2R
Funder
Bundesministerium für Bildung und Forschung BMBF (Deutschland)  
Conference
Intelligent Systems Conference (IntelliSys) 2020  
DOI
10.1007/978-3-030-55190-2_56
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • hyperbolic tangent

  • decision boundaries

  • neural network

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