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Machine Learning in Modeling and Simulation

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Cover of 'Machine Learning in Modeling and Simulation'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning in Computer Aided Engineering
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    Chapter 2 Artificial Neural Networks
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    Chapter 3 Gaussian Processes
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    Chapter 4 Machine Learning Methods for Constructing Dynamic Models From Data
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    Chapter 5 Physics-Informed Neural Networks: Theory and Applications
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    Chapter 6 Physics-Informed Deep Neural Operator Networks
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    Chapter 7 Digital Twin for Dynamical Systems
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    Chapter 8 Reduced Order Modeling
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    Chapter 9 Regression Models for Machine Learning
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    Chapter 10 Overview on Machine Learning Assisted Topology Optimization Methodologies
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    Chapter 11 Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering
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    Chapter 12 Machine Learning Interatomic Potentials: Keys to First-Principles Multiscale Modeling
Attention for Chapter 11: Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering
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Chapter title
Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering
Chapter number 11
Book title
Machine Learning in Modeling and Simulation
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-36644-4_11
Book ISBNs
978-3-03-136643-7, 978-3-03-136644-4
Authors

Huang, Tianyu, Bisram, Marisa, Li, Yang, Xu, Hongyi, Zeng, Danielle, Su, Xuming, Cao, Jian, Chen, Wei

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