Active-Learning-Driven Surrogate Modeling for Efficient Simulation of 
Parametric Nonlinear Systems

Kapadia, Harshit; Feng, Lihong; Benner, Peter

doi:10.1016/j.cma.2023.116657

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Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems

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Kapadia, Harshit
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Feng, Lihong
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Benner, Peter
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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https://zenodo.org/doi/10.5281/zenodo.10237734
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https://gitlab.mpi-magdeburg.mpg.de/kapadia/active-learning-surrogate-modeling
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2306.06174.pdf
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Citation

Kapadia, H., Feng, L., & Benner, P. (2024). Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems. Computer Methods in Applied Mechanics and Engineering, 419: 116657. doi:10.1016/j.cma.2023.116657.

Cite as: https://hdl.handle.net/21.11116/0000-000D-4DBC-A

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