Statistical Mechanics of Neural Networks is popular PDF and ePub book, written by Haiping Huang in 2022-01-04, 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 Mechanics of Neural Networks can be Read Online from any device for your convenience.
Statistical Mechanics of Neural Networks Book 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.
Detail Book of Statistical Mechanics of Neural Networks PDF
- Author : Haiping Huang
- Release : 04 January 2022
- Publisher : Springer Nature
- ISBN : 9789811675706
- Genre : Science
- Total Page : 302 pages
- Language : English
- PDF File Size : 7,6 Mb
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