Deep Learning and Physics (Mathematical Physics Studies) - Softcover

Buch 23 von 24: Mathematical Physics Studies

Tanaka, Akinori; Tomiya, Akio; Hashimoto, Koji

 
9789813361102: Deep Learning and Physics (Mathematical Physics Studies)
Softcover
ISBN 10: 9813361107 ISBN 13: 9789813361102
Verlag: Springer, 2022

Inhaltsangabe

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 providesprogress 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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Akinori Tanaka, Akio Tomiya, Koji Hashimoto

Von der hinteren Coverseite

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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2022
Sprache
Englisch
ISBN 10 
9813361107
ISBN 13 
9789813361102
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
224
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

Weitere beliebte Ausgaben desselben Titels

9789813361072: Deep Learning and Physics (Mathematical Physics Studies)

Vorgestellte Ausgabe

ISBN 10:  9813361077 ISBN 13:  9789813361072
Verlag: Springer, 2021
Hardcover