Sparse Grids and Applications - Stuttgart 2014

Author:   Jochen Garcke ,  Dirk Pflüger
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
Volume:   109
ISBN:  

9783319282602


Pages:   336
Publication Date:   18 March 2016
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Sparse Grids and Applications - Stuttgart 2014


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Author:   Jochen Garcke ,  Dirk Pflüger
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Volume:   109
Dimensions:   Width: 15.50cm , Height: 2.10cm , Length: 23.50cm
Weight:   6.506kg
ISBN:  

9783319282602


ISBN 10:   3319282603
Pages:   336
Publication Date:   18 March 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of 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.

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