Sparse grids and applications [electronic resource] : Stuttgart 2014 / Jochen Garcke, Kirk Pflüger, editor.
Garcke, Jochen, editor.; Pflüger, Dirk, editor.
2016
QA188
Available Online

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Title Sparse grids and applications [electronic resource] : Stuttgart 2014 / Jochen Garcke, Kirk Pflüger, editor.
ISBN 9783319282626 (electronic book)
331928262X (electronic book)
9783319282602
DOI https://doi.org/10.1007/978-3-319-28262-6
Published Cham, Switzerland : Springer, 2016.
Language English
Description 1 online resource : illustrations
Other Standard Identifiers 10.1007/978-3-319-28262-6 doi
Call Number QA188
Dewey Decimal Classification 004.36
Summary This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on sparse grids and applications. Sparse grids are a popular approach for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different guises, are frequently the method of choice, be it spatially adaptive in the hierarchical basis or via the dimensionally adaptive combination technique. Demonstrating once again the importance of this numerical discretization scheme, the selected articles present recent advances on the numerical analysis of sparse grids as well as efficient data structures. The book also discusses a range of applications, including uncertainty quantification and plasma physics.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Added Author Garcke, Jochen, editor.
Pflüger, Dirk, editor.
Series Lecture notes in computational science and engineering ; 109.
Available in Other Form Print version: 9783319282602
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Peng Chen and Christoph Schwab: Adaptive Sparse Grid Model Order Reduction for Fast Bayesian Estimation and Inversion
Fabian Franzelin and Dirk Pflüger: From Data to Uncertainty: An E_cient Integrated Data-Driven Sparse Grid Approach to Propagate Uncertainty
Helmut Harbrecht and Michael Peters: Combination Technique Based Second Moment Analysis for Elliptic PDEs on Random Domains
Brendan Harding: Adaptive sparse grids and extrapolation techniques
Philipp Hupp and Riko Jacob: A Cache-Optimal Alternative to the Unidirectional Hierarchization Algorithm
Valeriy Khakhutskyy and Markus Hegland: Spatially-Dimension- Adaptive Sparse Grids for Online Learning
Katharina Kormann and Eric Sonnendrücker: Sparse Grids for the Vlasov-Poisson Equation
Fabio Nobile, Lorenzo Tamellini, Francesco Tesei and Raul Tempone: An Adaptive Sparse Grid Algorithm for Elliptic PDEs with Lognormal Diffusion Coefficient
David Pfander, Alexander Heinecke, and Dirk Pflüger: A New Subspace-Based Algorithm for E_cient Spatially Adaptive Sparse Grid Regression, Classification and Multi- Evaluation
Sharif Rahman, Xuchun Ren, and Vaibhav Yadav: High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition
Jie Shen, Yingwei Wang, and Haijun Yu: E_cient Spectral-Element Methods for the Electronic Schrödinger Equation
Hoang Tran, Clayton G. Webster, and Guannan Zhang: A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models
Julian Valentin and Dirk Pflüger: Hierarchical Gradient-Based Optimization with BSplines on Sparse Grids.

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