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math-ph2026
Non-Intrusive Balancing for Data-Driven Model Reduction with Oblique Projections
Alberto Padovan
Non-intrusive reduced-order modeling is essential for systems simulated with black- or gray-box solvers, yet computing accurate data-driven models remains challenging when the dyna…
math-ph2024
Data-driven model reduction via non-intrusive optimization of projection operators and reduced-order dynamics
Alberto Padovan, Blaine Vollmer, Daniel J. Bodony
Computing reduced-order models using non-intrusive methods is particularly attractive for systems that are simulated using black-box solvers. However, obtaining accurate data-drive…