Context-aware learning of hierarchies of low-fidelity models for multi-fidelity 
uncertainty quantification

Farcas, I.-G.; Peherstorfer, B.; Neckel, T.; Jenko, F.; Bungartz, H.-J.

doi:10.1016/j.cma.2023.115908

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Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

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Jenko, F.
Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society;
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https://doi.org/10.1016/j.cma.2023.115908
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Farcas, I.-G., Peherstorfer, B., Neckel, T., Jenko, F., & Bungartz, H.-J. (2023). Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification. Computer Methods in Applied Mechanics and Engineering, 406: 115908. doi:10.1016/j.cma.2023.115908.

Cite as: https://hdl.handle.net/21.11116/0000-000C-A4B6-D

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