| 000 -LEADER |
|---|
| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
211022b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789813361072 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
530.0285 |
| Item number |
TAN |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Tanaka, Akinori |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Deep learning and physics |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2021 |
| Place of publication, distribution, etc |
Singapore : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiii, 207 p. ; |
| Other physical details |
ill., |
| Dimensions |
25 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
109.99 |
| Price type code |
EUR |
| Unit of pricing |
90.50 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Mathematical physics studies |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
What is deep learning for those who study physics? Is it completely different from physics? Or is it similar? In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is knowing physics useful in machine learning? Conversely, is knowing machine learning useful in physics? This book is devoted to answers of these questions. Starting with basic ideas of physics, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation of machine learning can be attributed to physical concepts. Hamiltonians that determine physical systems characterize various machine learning structures. Statistical physics given by Hamiltonians defines machine learning by neural networks. Furthermore, solving inverse problems in physics through machine learning and generalization essentially provides progress and even revolutions in physics. For these reasons, in recent years interdisciplinary research in machine learning and physics has been expanding dramatically. This book is written for anyone who wants to learn, understand, and apply the relationship between deep learning/machine learning and physics. All that is needed to read this book are the basic concepts in physics: energy and Hamiltonians. The concepts of statistical mechanics and the bracket notation of quantum mechanics, which are explained in columns, are used to explain deep learning frameworks. We encourage you to explore this new active field of machine learning and physics, with this book as a map of the continent to be explored. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
|
|---|
| Topical term or geographic name as entry element |
Physics |
|
|---|
| Topical term or geographic name as entry element |
Data processing |
|
|---|
| Topical term or geographic name as entry element |
Mathematical physics |
|
|---|
| Topical term or geographic name as entry element |
Deep learning |
|
|---|
| Topical term or geographic name as entry element |
Backpropogation method |
|
|---|
| Topical term or geographic name as entry element |
Bolzmann machine |
|
|---|
| Topical term or geographic name as entry element |
Chaos |
|
|---|
| Topical term or geographic name as entry element |
Contrastive divergence method |
|
|---|
| Topical term or geographic name as entry element |
Error Function |
|
|---|
| Topical term or geographic name as entry element |
Hamiltonian |
|
|---|
| Topical term or geographic name as entry element |
Ising model |
|
|---|
| Topical term or geographic name as entry element |
Lyapunov exponent |
|
|---|
| Topical term or geographic name as entry element |
Memory |
|
|---|
| Topical term or geographic name as entry element |
Metropolis test |
|
|---|
| Topical term or geographic name as entry element |
Partition function |
|
|---|
| Topical term or geographic name as entry element |
Quantum chromodynamics |
|
|---|
| Topical term or geographic name as entry element |
Restricted Boltzmann Machine |
|
|---|
| Topical term or geographic name as entry element |
Neural Network |
| 710 ## - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Tomiya, Akio |
|
|---|
| Corporate name or jurisdiction name as entry element |
Hashimoto, Koji |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |