Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference
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arXiv:2601.00038v2 Announce Type: replace Abstract: This work develops an active learning framework to intelligently enrich data-driven reduced-order models (ROMs) of parametric dynamical systems, which can serve as the foundation of virtual assets in a digital twin. Data-driven ROMs are explainabl…
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- 2026-09-04 04:00 · arXiv stat.ML
Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference