Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

DPD courier 4.99 € GLS courier 11.49 €

Contact

How to shop

Help

My account

▸ Empty :-(

DEEP LEARN METHOD MATHE PHY (V1)

Name: DEEP LEARN METHOD MATHE PHY (V1)
Brand: World Scientific Publishing Co Pte Ltd
SKU: 51430759
Price: 176.12 EUR
Availability: InStock
Author: CALIN OVIDIU
ISBN: 9789819827237

CALIN OVIDIU

Language

English

Book Hardback

Libristo code: 51430759

Publishers World Scientific Publishing Co Pte Ltd, March 2026

This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physi... Full description

Libristo code: 51430759

426 b

New

176.12 €

In stock at our supplier Shipping in 9-15 days

30-day return policy

Customers also purchased

Colis reassort tg b1 divers promo ete 1993 109vols Book

binding.

657.11 €

Defizite bei der Infrastruktur für Hygiene und Sanitärversorgung Abdoulaye Hassoumi Abdoulaye

Paperback

39.29 €

De Manet à Kelly.

Paperback

42.63 €

Rvr 1960 Biblia Económica de Evangelismo, Azul Tapa Rústica, Paquete de 20

Paperback

87.70 €

Digte: Gamle Og Nye... Andreas Munch

Paperback

23.08 €

DE AZULADAS TINTAS MARCHAL ESCABIAS MARIA JOSE

Paperback

19.44 €

Ceremonias de lo invisible David Oubina

Adobe ePub DRM

7.69 €

adventure of Dai. Dragon quest Riku Sanjo

Paperback

15.79 €

BABADADA black-and-white, Burmese (in burmese script) - Malti, visual dictionary (in burmese script) - dizzjunarju bl-istampi

Paperback

6.78 €

Nierozpraszalni. Jak panować nad uwagą i decydować o swoim życiu Nir Eyal

Paperback

10.02 €

Sümerler Helmut Uhlig

Paperback

25.11 €

Los fundamentos del fútbol, programa AT3, etapa de rendimiento : un nuevo concepto en el que fundamentar la formación del futbolista y el entrenamient César Frattarola Alcaraz

Paperback

81.52 €

Technik Der Emulsionen Otto Lange

Paperback

72.41 €

Bedeutung von Auslandsaufenthalten fur den Berufseinstieg Andy Schnackertz

Paperback

42.83 €

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.