gLaSDI: parametric physics-informed greedy latent space dynamics identification

DOI10.1016/j.jcp.2023.112267arXiv2204.12005OpenAlexW4379390621MaRDI QIDQ6107110

Xiaolong He, Jonathan L. Belof, William D. Fries, Jiun-Shyan Chen, Youngsoo Choi

Publication date: 3 July 2023

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2204.12005

zbMATH Keywords

nonlinear dynamical systemsadaptive samplingreduced order modelautoencodersphysics-informed greedy algorithmregression-based dynamics identification

Mathematics Subject Classification ID

Basic methods in fluid mechanics (76Mxx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Numerical methods for partial differential equations, boundary value problems (65Nxx)

Related Items

Adaptive learning of effective dynamics for online modeling of complex systems ⋮ GPLaSDI: Gaussian process-based interpretable latent space dynamics identification through deep autoencoder ⋮ Local Lagrangian reduced-order modeling for the Rayleigh-Taylor instability by solution manifold decomposition

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