Sparse Grids and Applications - Stuttgart 2014

Häftad, Engelska, 2018

Del 109 i serien Lecture Notes in Computational Science and Engineering

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2018-04-25
Mått:155 x 235 x 20 mm
Vikt:534 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computational Science and Engineering
Antal sidor:336
Förlag:Springer International Publishing AG
ISBN:9783319803098

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Matematikens grunder inom Naturvetenskap och teknik
Programmeringsböcker inom Data och IT

Innehållsförteckning

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.