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Data-Efficient Deep Operator Network for Unsteady Flow: A Multi-Fidelity Approach with Physics-Guided Subsampling

양선웅

제목: Data-Efficient Deep Operator Network for Unsteady Flow: A Multi-Fidelity Approach with Physics-Guided Subsampling

저자: 양선웅

DOI: 10.1016/j.cma.2025.118254

발행일: 2025-08

유형: 정기학술지(Article(Perspective Article포함))

저널명: Computer Methods in Applied Mechanics and Engineering