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cs.LG2026
In-context learning from self-generated trajectories for adaptive model reduction
Amirpasha Hedayat, Laura Balzano, Karthik Duraisamy
High-fidelity simulations of complex physical systems are often too expensive for repeated prediction, design, and control. Reduced-order models address this computational cost by…
cs.LG2026
History-aware adaptive reduced-order models via incremental singular value decomposition
Amirpasha Hedayat, Ali Mohaghegh, Laura Balzano +2
Reduced-order models (ROMs) can accelerate high-dimensional dynamical simulations, but their accuracy often deteriorates when online dynamics leave the regime represented by offlin…