2023
DOI: 10.48550/arxiv.2302.14526
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Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling

Abstract: In the framework of reduced basis methods, we recently introduced a new certified hierarchical and adaptive surrogate model, which can be used for efficient approximation of input-output maps that are governed by parametrized partial differential equations. This adaptive approach combines a full order model, a reduced order model and a machine-learning model. In this contribution, we extend the approach by leveraging novel kernel models for the machine learning part, especially structured deep kernel networks … Show more

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