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08 June 2022 11:00 - 13:00
Add Multi-fidelity methods for uncertainty quantification and optimization I Minisymposium organized by Lorenzo Tamellini, Matteo Diez, John Jakeman and Alex Gorodetsky |
Room: Spitsbergen MS39A Chair: Lorenzo Tamellini |
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Advanced Experiments on Gaussian Process-based Multi-fidelity Methods over Diverse Mathematical Characteristics
Sihmehmet Yildiz, Hayriye Pehlivan-Solak, Matteo Diez, Omer Goren and Melike Nikbay Multi-Fidelity Sparse Polynomial Chaos and Kriging Surrogate Models for Uncertainty Quantification Markus P. Rumpfkeil and Phil Beran Multifidelity ductile failure model by cokriging between simulations on unit cells and random microstructures Clément Cadet, Jacques Besson, Sylvain Flouriot, Samuel Forest, Pierre Kerfriden, Laurent Lacourt and Victor de Rancourt Domain-aware multifidelity learning for design optimization Francesco Di Fiore and Laura Mainini Multi-fidelity active learning for shape optimization problems affected by noise Jeroen Wackers, Riccardo Pellegrini, Matteo Diez, Andrea Serani and Michel Visonneau Comparing two multi-fidelity methods for forward uncertainty quantification of ship resistance Chiara Piazzola , Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani and Matteo Diez |
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