Emerging Trends in Machine Learning for Computational Fluid Dynamics
Author:
Affiliation:
1. KTH Royal Institute of Technology, Stockholm, Sweden
2. University of Washington, Seattle, WA, USA
Funder
European Research Council
U.S. Army Research Office
National Science Foundation AI Institute
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/5992/10124086/10124114.pdf?arnumber=10124114
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1. Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data
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