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Springer Deep Learning in Computational Mechanics: An Introductory Course

Amazon

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£81.12 £63.48 £67.33 £71.18 £75.02 £78.87 £82.72 25 July 2026 05 August 2026 16 August 2026 27 August 2026 08 September 2026
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Description

This book provides a first course without requiring prerequisite knowledge. Fundamental concepts of machine learning are introduced before explaining neural networks. With this knowledge, prominent topics in deep learning for simulation are explored. These include surrogate modeling, physics-informed neural networks, generative artificial intelligence, Hamiltonian/Lagrangian neural networks, input convex neural networks, and more general machine learning techniques. The idea of the book is to provide basic concepts as simple as possible but in a mathematically sound manner. Starting point are one-dimensional examples including elasticity, plasticity, heat evolution, or wave propagation. The concepts are then expanded to state-of-the-art applications in material modeling, generative artificial intelligence, topology optimization, defect detection, and inverse problems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
25 November 2025
Listed Since
03 March 2025

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