Sparse Grids and Applications - Stuttgart 2014 / edited by Jochen Garcke, Dirk Pflüger.

Format:

Book

Conference/Event

Contributor:

Garcke, Jochen., Editor.

Pflüger, Dirk., Editor.

Conference Name:

Workshop on Sparse Grids and Applications (3rd : 2014 : Universität Stuttgart), issuing body.

Series:

Lecture Notes in Computational Science and Engineering, 2197-7100 ; 109

Language:

English

Subjects (All):

Mathematics--Data processing.

Mathematics.

Algorithms.

Computational Science and Engineering.

Local Subjects:

Computational Science and Engineering.

Algorithms.

Physical Description:

1 online resource (348 p.)

Edition:

1st ed. 2016.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

Language Note:

English

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.

Contents:

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.

Notes:

Description based upon print version of record.

Includes bibliographical references.

ISBN:

3-319-28262-X

OCLC:

945095093