Deep Learning For Physics Research

Uwe Klemradt, Jonas Glombitza, Gregor Kasieczka, Martin Erdmann

ISBN 10: 981123745X / ISBN 13: 9789811237454

Editore: World Scientific Publishing Co Pte Ltd, SG, 2021

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A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.

Codice articolo LU-9789811237454

Dati bibliografici

• Titolo: Deep Learning For Physics Research
• Editore: World Scientific Publishing Co Pte Ltd, SG
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 981123745X
• ISBN 13: 9789811237454
• Rilegatura: Hardback
• Condizione: New
• Dimensioni: 15,24 L x 2,06 A x 22,86 P centimetri 15,24 centimetri di larghezza per 2,06 centimetri di altezza per 22,86 centimetri di profondità

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Riassunto

A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.