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Machine Learning in Modeling and Simulation

Overview of attention for book
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 3: Gaussian Processes
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