Titlebook: Statistical Mechanics of Neural Networks; Haiping Huang Book 2021 Higher Education Press 2021 Unsupervised Learning.Mean-field Theory.Cavi

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Book 2021 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..

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Monte Carlo Simulation Methods,ample, the Gibbs sampling is performed with the classical Monte Carlo methods or its variants with the help of importance sampling. In this chapter, we will introduce the basic knowledge about the sampling method and its applications to standard physics models.

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ks.Bridges old tools and frontiers in the theoretical develo.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 m

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,Variational Mean-Field Theory and Belief Propagation, model, and the approximation is equivalent to the Bethe approximation, which we shall provide an in-depth introduction in this chapter. In this chapter, we apply the variational method together with the mean-field approximation (MFA) and Bethe approximation (BA) to construct the free energy of the