Statistical Field Theory for Neural Networks is popular PDF and ePub book, written by Moritz Helias in 2020-08-20, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Statistical Field Theory for Neural Networks can be Read Online from any device for your convenience.
Statistical Field Theory for Neural Networks Book PDF Summary
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.
Detail Book of Statistical Field Theory for Neural Networks PDF
- Author : Moritz Helias
- Release : 20 August 2020
- Publisher : Springer Nature
- ISBN : 9783030464448
- Genre : Science
- Total Page : 203 pages
- Language : English
- PDF File Size : 12,8 Mb
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