Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems - Couverture souple

Calin, Ovidiu

 
9789819827923: Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Couverture souple
ISBN 10 : 9819827922 ISBN 13 : 9789819827923
Editeur : WSPC, 2026

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
WSPC
Date d'édition
2026
Langue
anglais
ISBN 10 
9819827922
ISBN 13 
9789819827923
Reliure
Broché
Nombre de pages
552
Coordonnées du fabricant
non disponible
Personne responsable
gpsr@libri.de
gpsr@libri.de

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