Iterative surrogate model optimization (ISMO): an active learning algorithm for PDE constrained optimization with deep neural networks

DOI10.1016/j.cma.2020.113575zbMath1506.65087arXiv2008.05730OpenAlexW3048421397MaRDI QIDQ2021252

Praveen Chandrashekar, Siddhartha Mishra, Deep Ray, Kjetil O. Lye

Publication date: 26 April 2021

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.05730

zbMATH Keywords

optimizationneural networksCFDdeep learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Numerical methods for mathematical programming, optimization and variational techniques (65K99) PDE constrained optimization (numerical aspects) (49M41)

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Uses Software

• SciPy
• redbKIT
• Python
• TensorFlow
• Keras
• Adam

Cites Work

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• Active Learning
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• Multidimensional Variation for Quasi-Monte Carlo
• Introduction to Genetic Algorithms
• Advanced Lectures on Machine Learning

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