DEEP LEARNING METHODS OF MATHEMATICAL PHYSICS - VOLUME I: DIRECT AND INVERSE PROBLEMS (Paperback)
Language: English
Published by World Scientific Publishing Co Pte Ltd, Singapore, 2026
- Softcover
- New
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
AbeBooks seller since June 22, 2007
Condition: New
£ 157.52
Quantity: 1 available
Add to basketItem description from seller
Paperback. This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physics, offering modern data-driven tools where traditional analytical and numerical methods fall short. As physical systems grow more complex or chaotic, deep learning provides efficient surrogates and physics-informed models capable of capturing dynamics and uncovering governing laws directly from data.This book introduces Neural ODEs, Physics-Informed Neural Networks (PINNs), and Hamiltonian and Lagrangian Neural Networks, showing how they enhance classical mechanics and PDE solvers for both forward and inverse problems. With Keras code examples, Google Colab notebooks, and practical exercises, this book serves researchers and students in physics, mathematics, and engineering seeking a concise, hands-on guide to applying deep learning in physical systems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Seller Inventory # 9789819827923
- Title
- DEEP LEARNING METHODS OF MATHEMATICAL PHYSICS - VOLUME I: DIRECT AND INVERSE PROBLEMS (Paperback)
- Author
- Ovidiu Calin
- Publisher
- World Scientific Publishing Co Pte Ltd, Singapore
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 9819827922
- ISBN 13
- 9789819827923
"Synopsis" may belong to another edition of this title.
AussieBookSeller
Truganina, VIC, Australia
AbeBooks seller since June 22, 2007
Shipping rates from Australia to U.S.A.
| Item | 25 to 45 business days | 8 to 14 business days |
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The Nile Group Pty Ltd
42 Apex Drive
Truganina, VIC Australia 3029
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