Description: Statistical Mechanics of Neural Networks Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Haiping Huang Format: Hardback Publisher: Springer Verlag, Singapore, Singapore Imprint: Springer Verlag, Singapore ISBN-13: 9789811675690, 978-9811675690 Synopsis 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.
Price: 104.29 GBP
Location: Aldershot
End Time: 2025-01-22T12:42:31.000Z
Shipping Cost: 30.66 GBP
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Book Title: Statistical Mechanics of Neural Networks
Publisher: Springer Verlag, Singapore
Item Height: 235 mm
Subject: Chemistry, Computer Science, Mathematics, Physics
Publication Year: 2022
Number of Pages: 280 Pages
Publication Name: Statistical Mechanics of Neural Networks
Language: English
Type: Textbook
Author: Haiping Huang
Item Width: 155 mm
Format: Hardcover
