1 citations · 1 across the 4 of their papers we have counts for
4 papers
Fast Quadratic Manifold Learning For Nonlinear Dimensionality Reduction in Large-scale Systems using Riemannian Optimization
Gavin Paxton, Seunghee Cheon, Rudy Geelen +1
The effectiveness of dimensionality reduction with quadratic manifolds hinges on the choice of a reduced basis and the associated quadratic correction terms. Existing approaches ty…
A Dynamic Subspace Approach for Low-rank Approximation of Large-scale Nonlinear Systems
Jack DeChant, Rudy Geelen, Shane A. McQuarrie +1
We present a dynamic subspace approach for efficiently approximating large-scale systems by learning time-continuous trajectories on the Grassmannian manifold. By parameterizing a…
Efficient data-driven regression for reduced-order modeling of spatial pattern formation
Alessandro Alla, Rudy Geelen, Hannah Lu
We present an efficient data-driven regression approach for constructing reduced-order models (ROMs) of reaction-diffusion systems exhibiting pattern formation. The ROMs are learne…
Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach
Jin Yi Yong, Rudy Geelen, Johann Guilleminot
This paper presents a probabilistic approach to represent and quantify model-form uncertainties in the reduced-order modeling of complex systems using operator inference techniques…