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 applica...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and hav...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
Sparse grids have gained increasing interest in recent years for the numerical treatment of high-dim...
Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where clas...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
getragenen Sonderforschungsbereiches 611 an der Universität Bonn ent-standen und als Manuskript verv...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional in...
High-dimensional problems pose a challenge for tomorrow’s supercomputing. Problems that require the ...
The area of interest for this study is the field of uncertainty quantification in computational flui...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and hav...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
Sparse grids have gained increasing interest in recent years for the numerical treatment of high-dim...
Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where clas...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
getragenen Sonderforschungsbereiches 611 an der Universität Bonn ent-standen und als Manuskript verv...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional in...
High-dimensional problems pose a challenge for tomorrow’s supercomputing. Problems that require the ...
The area of interest for this study is the field of uncertainty quantification in computational flui...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and hav...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...