Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" by S. A. McQuarrie, C. Huang, and K. E. Willcox.
Source code for the paper "Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference" by McQuarrie, Khodabakhshi, and Willcox
(MIRROR) Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
SR-OpInf: symmetry-reduced model reduction via operator inference
Source code for numerical experiments in the paper "Active learning for parametric differential systems with Bayesian operator inference" by McQuarrie, Guo, and Chaudhuri.
Complete implementation of Lift & Learn methodology for FitzHugh-Nagumo system with comprehensive visualizations and noise robustness analysis
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