Two new DOD-based reduced-order models (DOD-DL-ROM and DOD+DFNN) are introduced for hybrid-type parabolic PDEs, with rigorous error bounds linking performance to optimal map regularity and conditions for outperforming POD methods.
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2 Pith papers cite this work, alongside 86 external citations. Polarity classification is still indexing.
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2026 2verdicts
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Adaptive reduced-basis trust-region framework for efficient IRGNM-based defect identification in hyperbolic elastic systems, extending prior elliptic/parabolic work.
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A New Adaptive Deep Learning based Reduced Order Model for Hybrid-Type Parabolic PDEs: Rigorous Error Analysis and Applications
Two new DOD-based reduced-order models (DOD-DL-ROM and DOD+DFNN) are introduced for hybrid-type parabolic PDEs, with rigorous error bounds linking performance to optimal map regularity and conditions for outperforming POD methods.
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Adaptive Reduced-Basis Trust-Region Methods for Defect Identification in Elastic Materials
Adaptive reduced-basis trust-region framework for efficient IRGNM-based defect identification in hyperbolic elastic systems, extending prior elliptic/parabolic work.