26 citations
- Vietnam National University, HanoiVN5 papers
- Fraunhofer Institute for Algorithms and Scientific ComputingDE2 papers
- University of BonnDE2 papers
- Hanoi National University of EducationVN1 paper
- State University of New YorkUS1 paper
- University at Albany, State University of New YorkUS1 paper
- University of South CarolinaUS1 paper
- VNU University of ScienceVN1 paper
6 papers
-dimension in infinite dimensional hyperbolic cross approximation and application to parametric elliptic PDEs
Dinh Dũng, Michael Griebel, Vu Nhat Huy +1
In this article, we present a cost-benefit analysis of the approximation in tensor products of Hilbert spaces of Sobolev-analytic type. The Sobolev part is defined on a finite dime…
Approximation by translates of a single function of functions in space induced by the convolution with a given function
Dinh Dũng, Charles A. Micchelli, Vu Nhat Huy
We study approximation by arbitrary linear combinations of translates of a single function of periodic functions. We construct some methods of this approximation for functions…
Hyperbolic Cross Approximation
Dinh Dũng, Vladimir N. Temlyakov, Tino Ullrich
Hyperbolic cross approximation is a special type of multivariate approximation. Recently, driven by applications in engineering, biology, medicine and other areas of science new ch…
Gravity and nonabelian gauge fields in noncommutative space-time
Viet Ai Nguyen, Du Tien Pham
Noncommutative geometric construction of gravity in the two sheeted spacetime can be viewed as a discretized version of a Kaluza-Klein theory. In this paper, we show that it is pos…
Hyperbolic cross approximation in infinite dimensions
Dinh Dũng, Michael Griebel
We give tight upper and lower bounds of the cardinality of the index sets of certain hyperbolic crosses which reflect mixed Sobolev-Korobov-type smoothness and mixed Sobolev-analyt…
Sampling on energy-norm based sparse grids for the optimal recovery of Sobolev type functions in
Glenn Byrenheid, Dinh Dũng, Winfried Sickel +1
We investigate the rate of convergence of linear sampling numbers of the embedding . Here governs the mixed smoothness…