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Neural network models and deep learning.
Kriegeskorte, Nikolaus; Golan, Tal.
Affiliation
  • Kriegeskorte N; Department of Psychology, Columbia University, New York, NY 10027, USA; Department of Neuroscience, Columbia University, New York, NY 10027, USA; Department of Electrical Engineering, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA. Electronic address: n.kriegeskorte@columbia.edu.
  • Golan T; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA. Electronic address: tal.golan@columbia.edu.
Curr Biol ; 29(7): R231-R236, 2019 04 01.
Article in En | MEDLINE | ID: mdl-30939301
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Neural Networks, Computer / Deep Learning Limits: Animals / Humans Language: En Journal: Curr Biol Journal subject: BIOLOGIA Year: 2019 Document type: Article Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Neural Networks, Computer / Deep Learning Limits: Animals / Humans Language: En Journal: Curr Biol Journal subject: BIOLOGIA Year: 2019 Document type: Article Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM