Shane A. McQuarrie
Orcid: 0000-0003-0231-5359
According to our database1,
Shane A. McQuarrie authored at least 13 papers
between 2020 and 2026.
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Bibliography
2026
Fast Quadratic Manifold Learning For Nonlinear Dimensionality Reduction in Large-scale Systems using Riemannian Optimization.
CoRR, May, 2026
A Dynamic Subspace Approach for Low-rank Approximation of Large-scale Nonlinear Systems.
CoRR, May, 2026
Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference.
CoRR, January, 2026
2025
Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces.
CoRR, June, 2025
2024
Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems.
CoRR, 2024
2023
Nonintrusive Reduced-Order Models for Parametric Partial Differential Equations via Data-Driven Operator Inference.
SIAM J. Sci. Comput., August, 2023
2022
Concurrent MultiParameter Learning Demonstrated on the Kuramoto-Sivashinsky Equation.
SIAM J. Sci. Comput., 2022
2021
Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference.
CoRR, 2021
Concurrent multi-parameter learning demonstrated on the Kuramoto-Sivashinsky equation.
CoRR, 2021
2020
Data Assimilation in Large Prandtl Rayleigh-Bénard Convection from Thermal Measurements.
SIAM J. Appl. Dyn. Syst., 2020
Data-driven reduced-order models via regularized operator inference for a single-injector combustion process.
CoRR, 2020