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Statistical Field Theory for Neural Networks

By David Dahmen

Statistical Field Theory for Neural Networks

By David Dahmen

0 - Default Title
Description
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.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
224
Release Date:
2020-08-21
Publication Date:
2020-08-21
Publisher:
Springer
Languages:
Original: English
ISBN10:
3030464431
ISBN13:
9783030464431
GPSR Manufacturer Reference:
[email protected]
Weight:
347 g
Height:
155 cm
Width:
235 cm
Thickness:
13 cm
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