Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates

Author:

Brewer Wesley1ORCID,Martinez Daniel2ORCID,Gopalakrishnan Meena Muralikrishnan1ORCID,Kashi Aditya1ORCID,Borowiec Katarzyna1ORCID,Liu Siyan1ORCID,Pilmaier Christopher3ORCID,Burgreen Greg3ORCID,Bhushan Shanti3ORCID

Affiliation:

1. Oak Ridge National Laboratory, United States of America

2. Science & Technology Corporation, United States of America

3. Mississippi State University, United States of America

Funder

Department of Energy

Publisher

ACM

Reference38 articles.

1. Google AI. 2023. Time series forecasting. https://www.tensorflow.org/tutorials/structured_data/time_series Google AI. 2023. Time series forecasting. https://www.tensorflow.org/tutorials/structured_data/time_series

2. DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks

3. Gal Berkooz , Philip Holmes , and John  L. Lumley . 1993. The Proper Orthogonal Decomposition in the Analysis of Turbulent Flows. Annual Review of Fluid Mechanics 25 (Jan . 1993 ), 539–575. https://www.annualreviews.org/doi/abs/10.1146/annurev.fl.25.010193.002543 Gal Berkooz, Philip Holmes, and John L. Lumley. 1993. The Proper Orthogonal Decomposition in the Analysis of Turbulent Flows. Annual Review of Fluid Mechanics 25 (Jan. 1993), 539–575. https://www.annualreviews.org/doi/abs/10.1146/annurev.fl.25.010193.002543

4. Development and Validation of a Machine Learned Turbulence Model

5. Development of a Machine-Learned Cruise Guide Indicator for Rotorcraft

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