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Kniha DEEP LEARN METHOD MATHE PHY (V1) CALIN OVIDIU

DEEP LEARN METHOD MATHE PHY (V1)

Autor: CALIN OVIDIU
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: World Scientific Publishing Co Pte Ltd
Dostupnost: Skladem u dodavatele
Odesíláme za 9-15 dnů
2 083 Kč
This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physi...

Informace o knize

Autor
CALIN OVIDIU
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2026
Stránek
554
EAN
9789819827923
ISBN
9819827922
Enbook ID
51430762
Vydavatel
World Scientific Publishing Co Pte Ltd
Hmotnost
733
Rozměry
152 x 229 x 29

Kompletní popis

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.

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