Statistical Field Theory for Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Field Theory for Neural Networks write by Moritz Helias. This book was released on 2020-08-20. Statistical Field Theory for Neural Networks available in PDF, EPUB and Kindle. 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.
Statistical Mechanics of Neural Networks
Statistical Mechanics of Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Mechanics of Neural Networks write by Haiping Huang. This book was released on 2021. Statistical Mechanics of Neural Networks available in PDF, EPUB and Kindle. 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.
Statistical Mechanics of Neural Networks
Statistical Mechanics of Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Mechanics of Neural Networks write by Haiping Huang. This book was released on 2022-01-04. Statistical Mechanics of Neural Networks available in PDF, EPUB and Kindle. 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.
Neural Network Modeling
Neural Network Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Modeling write by P. S. Neelakanta. This book was released on 2018-02-06. Neural Network Modeling available in PDF, EPUB and Kindle. Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.
The Principles of Deep Learning Theory
The Principles of Deep Learning Theory - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Principles of Deep Learning Theory write by Daniel A. Roberts. This book was released on 2022-05-26. The Principles of Deep Learning Theory available in PDF, EPUB and Kindle. This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
