From Data to Uncertainty: An Efficient Integrated Data-Driven Sparse Grid Approach to Propagate Uncertainty

DOI10.1007/978-3-319-28262-6_2zbMath1339.65018OpenAlexW2476662660MaRDI QIDQ2808016

Dirk Pflüger, Fabian Franzelin

Publication date: 26 May 2016

Published in: Lecture Notes in Computational Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-28262-6_2

zbMATH Keywords

algorithmuncertaintynumerical examplecollocation methodsparse gridmoment estimationsubsurface flow problem

Mathematics Subject Classification ID

Related Items (4)

Convergence analysis of multifidelity Monte Carlo estimation ⋮ Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario ⋮ Gradient-Based Two-Scale Topology Optimization With B-Splines on Sparse Grids ⋮ Heterogeneous distributed big data clustering on sparse grids

Uses Software

• libagf

Cites Work

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