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Neuromanifolds

  • Ovidiu CalinEmail author
Chapter
  • 39 Downloads
Part of the Springer Series in the Data Sciences book series (SSDS)

Abstract

In this chapter we shall approach the study of neural networks from the Information Geometry perspective. This applies both techniques of Differential Geometry and Probability Theory to neural networks.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematics & StatisticsEastern Michigan UniversityYpsilantiUSA

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