Operator Inference and Physics-Informed Learning of Low-Dimensional Models for 
Incompressible Flows

Benner, Peter; Goyal, Pawan Kumar; Heiland, Jan; Pontes Duff, Igor

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Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows

Benner, P., Goyal, P. K., Heiland, J., & Pontes Duff, I. (in preparation). Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0007-378A-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-534C-6

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Creators:
Benner, Peter^{1, 2}, Author
Goyal, Pawan Kumar¹, Author
Heiland, Jan^{1, 2}, Author
Pontes Duff, Igor¹, Author

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1Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738141
2OvGU, ou_persistent22

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Dates: Created: 2020-10-13

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Identifiers: arXiv: 2010.06701

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