Pages that link to "Item:Q2222574"
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The following pages link to Uncertainty quantification of discontinuous outputs via a non-intrusive bifidelity strategy (Q2222574):
Displaying 8 items.
- Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction (Q725460) (← links)
- Machine learning for flux regression in discrete fracture networks (Q2059207) (← links)
- Discontinuous neural networks and discontinuity learning (Q2088828) (← links)
- 3D-1D coupling on non conforming meshes via a three-field optimization based domain decomposition (Q2134518) (← links)
- Uncertainty quantification analysis in discrete fracture network flow simulations (Q2176416) (← links)
- Multifidelity framework for uncertainty quantification with multiple quantities of interest (Q2185990) (← links)
- A robust VEM-based approach for flow simulations in poro-fractured media (Q5024417) (← links)
- Deep Neural Network Surrogates for Nonsmooth Quantities of Interest in Shape Uncertainty Quantification (Q5097855) (← links)
