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Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

E. Qian
Boris Kramer
Benjamin Peherstorfer
Karen E. Willcox
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Papers citing "Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems"

3 / 3 papers shown
Title
Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine
Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine
Ionut-Gabriel Farcas
Rayomand P. Gundevia
R. Munipalli
Karen E. Willcox
AI4CE
102
1
0
13 Jul 2024
Sampling low-dimensional Markovian dynamics for pre-asymptotically recovering reduced models from data with operator inference
Sampling low-dimensional Markovian dynamics for pre-asymptotically recovering reduced models from data with operator inference
Benjamin Peherstorfer
28
50
0
29 Aug 2019
Kernel Methods for the Approximation of Nonlinear Systems
Kernel Methods for the Approximation of Nonlinear Systems
J. Bouvrie
B. Hamzi
108
57
0
14 Aug 2011

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