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Automatic Proper Orthogonal Block Decomposition method for network dynamical systems with multiple timescales
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An adaptive model order reduction technique for parameter-dependent modular structures
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Physics-informed two-tier neural network for non-linear model order reduction
ROSE: A reduced-order scattering emulator for optical models
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MCMS-RBM: Multicomponent Multistate Reduced Basis Method Toward Rapid Generation of Phase Diagrams for the Lifshitz–Petrich Model
Optimizing near-carbon-free nuclear energy systems: advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation
Multi‐fidelity error estimation accelerates greedy model reduction of complex dynamical systems
Lihong Feng, Luigi Lombardi, Giulio Antonini and Peter Benner International Journal for Numerical Methods in Engineering 124(23) 5312 (2023) https://doi.org/10.1002/nme.7348
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Non-Intrusive Reduced-Order Modeling Based on Parametrized Proper Orthogonal Decomposition
Model order reduction for deforming domain problems in a time‐continuous space‐time setting
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Multiscale model reduction for stochastic elasticity problems using ensemble variable-separated method
Lookahead data-gathering strategies for online adaptive model reduction of transport-dominated problems
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BUQEYE guide to projection-based emulators in nuclear physics
Jan G. Korvink, Kirill V. Poletkin, Yongbo Deng and Lihong Feng Springer Handbooks, Springer Handbook of Semiconductor Devices 1303 (2023) https://doi.org/10.1007/978-3-030-79827-7_36
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An EIM-based compression-extrapolation tool for efficient treatment of homogenized cross-section data
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Proper orthogonal descriptors for efficient and accurate interatomic potentials