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Statistical Field Theory for Neural Networks

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Artikelnr: SK0274943-SE20260527-055838 Kategori: Etikett:

Beskrivning

Beskrivning

This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks.

This book is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra.

Om boken

Om denna bok

Statistical Field Theory for Neural Networks av Moritz Helias och David Dahmen är en Häftad bok med 203 sidor på Engelska. Detta är den 1:a upplagan som utgavs 2020 av Springer Nature.

Produktinformation

Kategori
Okänd
Bandtyp
Häftad
Språk
Engelska
ISBN
9783030464431
Upplaga
1
Utgiven
2020-08-21
Förlag
Springer Nature
Sidantal
203