Browsing Publikasjoner fra CRIStin by Subject "Data-driven modeling"
Now showing items 1-2 of 2
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Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
(Peer reviewed; Journal article, 2022)Upcoming technologies like digital twins, autonomous, and artificial intelligent systems involving safety–critical applications require accurate, interpretable, computationally efficient, and generalizable models. ... -
Nonlinear proper orthogonal decomposition for convection-dominated flows
(Peer reviewed; Journal article, 2021)Autoencoder techniques find increasingly common use in reduced order modeling as a means to create a latent space. This reduced order representation offers a modular data-driven modeling approach for nonlinear dynamical ...