8 citations · 8 across the 4 of their papers we have counts for
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cs.CE2025
Optimal Experimental Design of a Moving Sensor for Linear Bayesian Inverse Problems
Nicole Aretz, Thomas Lynn, Karen Willcox +1
We optimize the path of a mobile sensor to minimize the posterior uncertainty of a Bayesian inverse problem. Along its path, the sensor continuously takes measurements of the state…
cs.LG2025
Nested Operator Inference for Adaptive Data-Driven Learning of Reduced-order Models
Nicole Aretz, Karen Willcox
This paper presents a data-driven, nested Operator Inference (OpInf) approach for learning physics-informed reduced-order models (ROMs) from snapshot data of high-dimensional dynam…
math.DS2025★ 8 cited
Non-intrusive reduced-order modeling for dynamical systems with spatially localized features
Leonidas Gkimisis, Nicole Aretz, Marco Tezzele +3
This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed…