71 citations · 141 across the 11 of their papers we have counts for
12 papers
Structure-Informed Data-Driven Reduced-Order Modeling of Scalar Hyperbolic Conservation Laws via Kinetic Defect Measure
Marissa Llamas, Jan Fuhg, Hannah Lu
Reduced-order modeling of transport-dominated systems remains challenging because moving fronts and shocks are poorly represented by low-dimensional linear subspaces. We develop a…
Data-Driven Modeling and Correction of Vehicle Dynamics
Nguyen Ly, Caroline Tatsuoka, Jai Nagaraj +4
We develop a data-driven framework for learning and correcting non-autonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exh…
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 Nonautonomous Systems via Dynamic Mode Decomposition
Hannah Lu, Daniel M. Tartakovsky
We present a data-driven learning approach for unknown nonautonomous dynamical systems with time-dependent inputs based on dynamic mode decomposition (DMD). To circumvent the diffi…
Model Reduction via Dynamic Mode Decomposition
Hannah Lu, Daniel M. Tartakovsky
This work proposes a new framework of model reduction for parametric complex systems. The framework employs a popular model reduction technique dynamic mode decomposition (DMD), wh…
Machine Learning in Heterogeneous Porous Materials
Marta D'Elia, Hang Deng, Cedric Fraces +21
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material scienc…