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References

This page contains the literature and external references cited along the toolbox documentation or supporting materials. For a full bibtex file for citing them, please check this database file.

[1]
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L. Lu, X. Meng, Z. Mao and G. E. Karniadakis. DeepXDE: A Deep Learning Library for Solving Differential Equations. SIAM Review 63, 208–228 (2021).
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L. Lu, R. Pestourie, W. Yao, Z. Wang, F. Verdugo and S. G. Johnson. Physics-informed neural networks with hard constraints for inverse design, arXiv (2021).
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M. A. Nabian, R. J. Gladstone and H. Meidani. Efficient training of physics‐informed neural networks via importance sampling. Computer-Aided Civil and Infrastructure Engineering 36, 962–977 (2021).
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S. Sanyal and K. Roy. RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network, arXiv (2022).
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T. Würth, C. Krauß, C. Zimmerling and L. Kärger. Physics-informed neural networks for data-free surrogate modelling and engineering optimization – An example from composite manufacturing. Materials & Design 231, 112034 (2023).
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