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Statistical mechanics of neural networks / Haiping Huang.

SpringerLink Books Physics and Astronomy eBooks 2021 Available online

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Format:
Book
Author/Creator:
Huang, Haiping, author.
Language:
English
Subjects (All):
Neural networks (Computer science)--Statistical methods.
Neural networks (Computer science).
Genre:
Electronic books.
Physical Description:
1 online resource (302 pages) : illustrations (some color)
Place of Publication:
Singapore : Springer, [2021]
System Details:
text file PDF
Summary:
This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks. The book discusses in details important concepts and techniques including the cavity method, the mean-field theory, replica techniques, the Nishimori condition, variational methods, the dynamical mean-field theory, unsupervised learning, associative memory models, perceptron models, the chaos theory of recurrent neural networks, and eigen-spectrums of neural networks, walking new learners through the theories and must-have skillsets to understand and use neural networks. The book focuses on quantitative frameworks of neural network models where the underlying mechanisms can be precisely isolated by physics of mathematical beauty and theoretical predictions. It is a good reference for students, researchers, and practitioners in the area of neural networks.
Contents:
Introduction
Spin glass models and cavity method
Variational mean-eld theory and belief propagation
Monte Carlo simulation methods
High-temperature expansion
Nishimori line
Random energy model
Statistical mechanical theory of Hopeld model
Replica symmetry and replica symmetry breaking
Statistical mechanics of restricted Boltzmann machine
Simplest model of unsupervised learning with binary synapses
Inherent-symmetry breaking in unsupervised learning
Mean-eld theory of Ising Perceptron
Mean-eld model of multi-layered Perceptron
Mean-eld theory of dimension reduction
Chaos theory of random recurrent neural networks
Statistical mechanics of random matrices
Perspectives.
Notes:
Includes bibliographical references.
Description based on online resource; title from digital title page (viewed on January 25, 2022).
Other Format:
Print version: Huang, Haiping Statistical Mechanics of Neural Networks
ISBN:
9789811675706
9811675708
OCLC:
1291317829
Access Restriction:
Restricted for use by site license.

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