Contact
How to shop
Delivery
Shopping guide
DEEP LEARN METHOD MATHE PHY (V1)
English
235 b
Delivery to Austria
Up to 30 days for returns
Customers also purchased
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.
About the book
English
Categories
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressYou might also be interested in
/
Hardback
21.49
€
/
Hardback
135.59
€
/
Hardback
128.69
€
Hi! I'm Libroamiko, your book advisor.
How can I help you?