Pages that link to "Item:Q2072456"
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The following pages link to Projection-based model reduction of dynamical systems using space-time subspace and machine learning (Q2072456):
Displaying 13 items.
- Applied unsupervised learning in model reduction of linear dynamic systems (Q679283) (← links)
- Projection-based model reduction: formulations for physics-based machine learning (Q1739759) (← links)
- Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold (Q2020284) (← links)
- Physics-informed machine learning models for predicting the progress of reactive-mixing (Q2021234) (← links)
- Time-series machine-learning error models for approximate solutions to parameterized dynamical systems (Q2184303) (← links)
- LaSDI: parametric latent space dynamics identification (Q2674132) (← links)
- An online manifold learning approach for model reduction of dynamical systems (Q2927840) (← links)
- A Fast Time-Stepping Strategy for Dynamical Systems Equipped with a Surrogate Model (Q5864692) (← links)
- A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems (Q6076407) (← links)
- Non-intrusive model order reduction for parametric radiation transport simulations (Q6078480) (← links)
- gLaSDI: parametric physics-informed greedy latent space dynamics identification (Q6107110) (← links)
- Parametric nonlinear model reduction using machine learning on Grassmann manifold with an application on a flow simulation (Q6536761) (← links)
- A deep learning -- genetic algorithm approach for aerodynamic inverse design via optimization of pressure distribution (Q6588345) (← links)
