Deep learning in fluid dynamics von Kutz, J. Nathan

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Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control von Brunton, Steven L., Kutz, J. Nathan

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Data-driven discovery of coordinates and governing equations von Champion, Kathleen, Lusch, Bethany, Kutz, J. Nathan, Brunton, Steven L.

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Sparse identification of nonlinear dynamics for rapid model recovery von Quade, Markus, Abel, Markus, Nathan Kutz, J., Brunton, Steven L.

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Deep learning for universal linear embeddings of nonlinear dynamics von Lusch, Bethany, Kutz, J. Nathan, Brunton, Steven L.

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Discovering governing equations from data by sparse identification of nonlinear dynamical systems von Brunton, Steven L., Proctor, Joshua L., Kutz, J. Nathan

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Chaos as an intermittently forced linear system von Brunton, Steven L., Brunton, Bingni W., Proctor, Joshua L., Kaiser, Eurika, Kutz, J. Nathan

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Sparse identification of nonlinear dynamics for model predictive control in the low-data limit von Kaiser, E., Kutz, J. N., Brunton, S. L.

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Deep learning of dynamics and signal-noise decomposition with time-stepping constraints von Rudy, Samuel H., Nathan Kutz, J., Brunton, Steven L.

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Forecasting dengue fever in Brazil: An assessment of climate conditions von Stolerman, Lucas M, Maia, Pedro D, Kutz, J Nathan

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DeepGreen: deep learning of Green’s functions for nonlinear boundary value problems von Gin, Craig R., Shea, Daniel E., Brunton, Steven L., Kutz, J. Nathan

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Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control von Brunton, Steven L, Brunton, Bingni W, Proctor, Joshua L, Kutz, J Nathan

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Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning von Brunton, Steven L, Nathan Kutz, J, Manohar, Krithika, Aravkin, Aleksandr Y, Morgansen, Kristi, Klemisch, Jennifer, Goebel, Nicholas, Buttrick, James, Poskin, Jeffrey, Blom-Schieber, Adriana W, Hogan, Thomas, McDonald, Darren

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Modeling thermodynamic trends of rotating detonation engines von Koch, James, Kutz, J. Nathan

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Machine learning for parameter estimation von Kutz, J Nathan

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SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics von Kaheman, Kadierdan, Kutz, J. Nathan, Brunton, Steven L.

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Data-driven discovery of Koopman eigenfunctions for control von Kaiser, Eurika, Kutz, J Nathan, Brunton, Steven L

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Learning dominant physical processes with data-driven balance models von Callaham, Jared L., Koch, James V., Brunton, Bingni W., Kutz, J. Nathan, Brunton, Steven L.

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Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition von Brunton, Bingni W., Johnson, Lise A., Ojemann, Jeffrey G., Kutz, J. Nathan

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Greedy Sensor Placement With Cost Constraints von Clark, Emily, Askham, Travis, Brunton, Steven L., Nathan Kutz, J.

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