6 citations · 8 across the 5 of their papers we have counts for
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cs.LG2026★ 6 cited
High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics
Diana A. Bistrian
The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e., not requiring Galerkin proj…
math.NA2026
Hankel-Koopman Finite-Horizon Energy Decomposition of Coupled Experimental Data: A Three-Phase Data-Driven Twin Forecasting Framework
Diana A. Bistrian, Marcel Topor
This paper introduces a unified three-phase data-driven twin framework for finite-horizon forecasting of physical quantities from coupled experimental measurements. The framework c…