Search Results - "Brunton, L L"

Machine Learning for Fluid Mechanics by Brunton, Steven L, Noack, Bernd R, Koumoutsakos, Petros

“…The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at…”
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Deep learning for universal linear embeddings of nonlinear dynamics by Lusch, Bethany, Kutz, J. Nathan, Brunton, Steven L.

“…Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation,…”
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Applying machine learning to study fluid mechanics by Brunton, Steven L.

“…This paper provides a short overview of how to use machine learning to build data-driven models in fluid mechanics. The process of machine learning is broken…”
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Discovering governing equations from data by sparse identification of nonlinear dynamical systems by Brunton, Steven L., Proctor, Joshua L., Kutz, J. Nathan

“…Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain…”
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Sparse identification of nonlinear dynamics for model predictive control in the low-data limit by Kaiser, E., Kutz, J. N., Brunton, S. L.

“…Data-driven discovery of dynamics via machine learning is pushing the frontiers of modelling and control efforts, providing a tremendous opportunity to extend…”
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Data-driven discovery of coordinates and governing equations by Champion, Kathleen, Lusch, Bethany, Kutz, J. Nathan, Brunton, Steven L.

“…The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative…”
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Data-driven discovery of Koopman eigenfunctions for control by Kaiser, Eurika, Kutz, J Nathan, Brunton, Steven L

“…Abstract Data-driven transformations that reformulate nonlinear systems in a linear framework have the potential to enable the prediction, estimation, and…”
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Chaos as an intermittently forced linear system by Brunton, Steven L., Brunton, Bingni W., Proctor, Joshua L., Kaiser, Eurika, Kutz, J. Nathan

“…Understanding the interplay of order and disorder in chaos is a central challenge in modern quantitative science. Approximate linear representations of…”
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Optimal Sensor and Actuator Selection Using Balanced Model Reduction by Manohar, Krithika, Kutz, J. Nathan, Brunton, Steven L.

“…Optimal sensor and actuator selection is a central challenge in high-dimensional estimation and control. Nearly all subsequent control decisions are affected…”
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Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control by Brunton, Steven L, Brunton, Bingni W, Proctor, Joshua L, Kutz, J Nathan

“…In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant…”
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DeepGreen: deep learning of Green’s functions for nonlinear boundary value problems by Gin, Craig R., Shea, Daniel E., Brunton, Steven L., Kutz, J. Nathan

“…Boundary value problems (BVPs) play a central role in the mathematical analysis of constrained physical systems subjected to external forces. Consequently,…”
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A Unified Framework for Sparse Relaxed Regularized Regression: SR3 by Zheng, Peng, Askham, Travis, Brunton, Steven L., Kutz, J. Nathan, Aravkin, Aleksandr Y.

“…Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression, in particular, has been…”
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Learning dominant physical processes with data-driven balance models by Callaham, Jared L., Koch, James V., Brunton, Bingni W., Kutz, J. Nathan, Brunton, Steven L.

“…Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant…”
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Special issue on machine learning and data-driven methods in fluid dynamics by Brunton, Steven L., Hemati, Maziar S., Taira, Kunihiko

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Towards extending the aircraft flight envelope by mitigating transonic airfoil buffet by Lagemann, Esther, Brunton, Steven L., Schröder, Wolfgang, Lagemann, Christian

“…In the age of globalization, commercial aviation plays a central role in maintaining our international connectivity by providing fast air transport services…”
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A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data by Champion, Kathleen, Zheng, Peng, Aravkin, Aleksandr Y., Brunton, Steven L., Kutz, J. Nathan

“…Machine learning (ML) is redefining what is possible in data-intensive fields of science and engineering. However, applying ML to problems in the physical…”
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Mobile Sensor Path Planning for Kalman Filter Spatiotemporal Estimation by Mei, Jiazhong, Brunton, Steven L, Kutz, J Nathan

“…The estimation of spatiotemporal data from limited sensor measurements is a required task across many scientific disciplines. In this paper, we consider the…”
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Cyclic nucleotide research - still expanding after half a century by Beavo, Joseph A, Brunton, Laurence L

“…Since the discovery in 1957 that cyclic AMP acts as a second messenger for the hormone adrenaline, interest in this molecule and its companion, cyclic GMP, has…”
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Sparse nonlinear models of chaotic electroconvection by Guan, Yifei, Brunton, Steven L, Novosselov, Igor

“…Convection is a fundamental fluid transport phenomenon, where the large-scale motion of a fluid is driven, for example, by a thermal gradient or an electric…”
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Bilinear dynamic mode decomposition for quantum control by Goldschmidt, Andy, Kaiser, E, DuBois, J L, Brunton, S L, Kutz, J N

“…Abstract Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems…”
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