PDE-DKL: PDE-constrained deep kernel learning in high dimensionality

Many physics-informed machine learning methods for PDE-based problems rely on Gaussian processes (GPs) or neural networks (NNs). However, both face limitations when data are scarce and the dimensionality is high. Although GPs are known for their robust uncertainty quantification in low-dimensional s...

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Bibliographic Details
Main Authors Yan, Weihao, Brune, Christoph, Guo, Mengwu
Format Journal Article
LanguageEnglish
Published 30.01.2025
Subjects
Online AccessGet full text
DOI10.48550/arxiv.2501.18258

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