Neural network models and deep learning

Nikolaus Kriegeskorte, Tal Golan

Research output: Contribution to journalShort surveypeer-review

210 Scopus citations

Abstract

Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence. They can approximate functions and dynamics by learning from examples. Here we give a brief introduction to neural network models and deep learning for biologists. We introduce feedforward and recurrent networks and explain the expressive power of this modeling framework and the backpropagation algorithm for setting the parameters. Finally, we consider how deep neural network models might help us understand brain computation.

Original languageEnglish
Pages (from-to)R231-R236
JournalCurrent Biology
Volume29
Issue number7
DOIs
StatePublished - 1 Apr 2019
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (all)
  • Agricultural and Biological Sciences (all)

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