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Könyv DEEP LEARN METHOD MATHE PHY (V1) CALIN OVIDIU

DEEP LEARN METHOD MATHE PHY (V1)

Szerző: CALIN OVIDIU
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: World Scientific Publishing Co Pte Ltd
Elérhetőség: Beszállítói készleten
Küldés 14-21 napon belül
34 044 Ft
This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physi...

Információk a könyvről

Szerző
CALIN OVIDIU
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2026
oldal
554
EAN
9789819827923
ISBN
9819827922
Enbook ID
51430762
Kiadó
World Scientific Publishing Co Pte Ltd
Súly
733
Méretek
152 x 229 x 29

Teljes leírás

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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