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Michael D. Graham

On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions

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Nov 20, 2024
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Data-driven low-dimensional model of a sedimenting flexible fiber

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May 16, 2024
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Building symmetries into data-driven manifold dynamics models for complex flows

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Dec 15, 2023
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Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches

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Oct 10, 2023
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Autoencoders for discovering manifold dimension and coordinates in data from complex dynamical systems

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May 01, 2023
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Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning

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Jan 28, 2023
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Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow

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Jan 11, 2023
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Deep learning delay coordinate dynamics for chaotic attractors from partial observable data

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Nov 20, 2022
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Data-driven low-dimensional dynamic model of Kolmogorov flow

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Oct 29, 2022
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Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning

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May 01, 2022
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