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Deep Learning and Physics
Akinori Tanaka, Akio Tomiya, Koji Hashimoto (Broschiert, Englisch)
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Beschreibung
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. 85,59 €
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Technische Daten
Erscheinungsdatum
22.02.2022
Sprache
Englisch
EAN
9789813361102
Herausgeber
Springer Singapore
Serien- oder Bandtitel
Mathematical Physics Studies
Sonderedition
Nein
Autor
Akinori Tanaka, Akio Tomiya, Koji Hashimoto
Seitenanzahl
207
Einbandart
Broschiert
Autorenporträt
Akinori Tanaka, Akio Tomiya, Koji Hashimoto
Schlagwörter
Deep learning, Physics, Neural network, Applications to theoretical physics, Machine learning
Thema-Inhalt
PHU - Mathematische Physik
UYQM - Maschinelles Lernen
PHS - Statistische Physik
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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