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Sparse Grids and Applications - Stuttgart 2014

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Jochen Garcke

    1. Institut für Numerische Simulation, Universität Bonn, Bonn, Germany

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  2. Dirk Pflüger

    1. Institute for Parallel and Distributed S, Universität Stuttgart, Stuttgart, Germany

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 109)

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Table of contents (13 papers)

  1. Front Matter

    Pages i-viii
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  2. Adaptive Sparse Grid Model Order Reduction for Fast Bayesian Estimation and Inversion

    • Peng Chen, Christoph Schwab
    Pages 1-27

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

    • Fabian Franzelin, Dirk Pflüger
    Pages 29-49

  4. Combination Technique Based Second Moment Analysis for Elliptic PDEs on Random Domains

    • Helmut Harbrecht, Michael Peters
    Pages 51-77

  5. Adaptive Sparse Grids and Extrapolation Techniques

    • Brendan Harding
    Pages 79-102

  6. A Cache-Optimal Alternative to the Unidirectional Hierarchization Algorithm

    • Philipp Hupp, Riko Jacob
    Pages 103-132

  7. Spatially-Dimension-Adaptive Sparse Grids for Online Learning

    • Valeriy Khakhutskyy, Markus Hegland
    Pages 133-162

  8. Sparse Grids for the Vlasov–Poisson Equation

    • Katharina Kormann, Eric Sonnendrücker
    Pages 163-190

  9. An Adaptive Sparse Grid Algorithm for Elliptic PDEs with Lognormal Diffusion Coefficient

    • Fabio Nobile, Lorenzo Tamellini, Francesco Tesei, Raúl Tempone
    Pages 191-220

  10. A New Subspace-Based Algorithm for Efficient Spatially Adaptive Sparse Grid Regression, Classification and Multi-evaluation

    • David Pfander, Alexander Heinecke, Dirk Pflüger
    Pages 221-246

  11. High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition

    • Sharif Rahman, Xuchun Ren, Vaibhav Yadav
    Pages 247-264

  12. Efficient Spectral-Element Methods for the Electronic Schrödinger Equation

    • Jie Shen, Yingwei Wang, Haijun Yu
    Pages 265-289

  13. A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models

    • Hoang Tran, Clayton G. Webster, Guannan Zhang
    Pages 291-313

  14. Hierarchical Gradient-Based Optimization with B-Splines on Sparse Grids

    • Julian Valentin, Dirk Pflüger
    Pages 315-336

  15. Back Matter

    Pages 337-344
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Keywords

About this book

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.

Editors and Affiliations

  • Institut für Numerische Simulation, Universität Bonn, Bonn, Germany

    Jochen Garcke

  • Institute for Parallel and Distributed S, Universität Stuttgart, Stuttgart, Germany

    Dirk Pflüger

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