[1] |
M. Griebel, A. Hullmann, and P. Oswald.
Optimal scaling parameters for sparse grid discretizations.
Numerical Linear Algebra with Applications, 22(1):76-100,
2015.
Also available as INS Preprint No. 1314. [ bib | DOI | http | .pdf 1 ] |
[2] |
A. Hullmann.
The ANOVA decomposition and generalized sparse grid methods for
the high-dimensional backward Kolmogorov equation.
Dissertation, Institut für Numerische Simulation, Universität
Bonn, 2015. [ bib | .pdf (link) ] |
[3] |
M. Griebel and A. Hullmann.
A sparse grid based generative topographic mapping for the
dimensionality reduction of high-dimensional data.
In H. Bock, X. Hoang, R. Rannacher, and J. Schlöder, editors,
Modeling, Simulation and Optimization of Complex Processes - HPSC 2012,
pages 51-62. Springer International Publishing, 2014.
Also available as INS Preprint No. 1206. [ bib | DOI | http | .pdf 1 ] |
[4] |
M. Griebel and A. Hullmann.
On a multilevel preconditioner and its condition numbers for the
discretized Laplacian on full and sparse grids in higher dimensions.
In Singular Phenomena and Scaling in Mathematical Models, pages
263-296. Springer International Publishing Switzerland, 2014.
Also available as INS Preprint No. 1301. [ bib | .pdf 1 ] |
[5] |
M. Griebel and A. Hullmann.
Dimensionality reduction of high-dimensional data with a nonlinear
principal component aligned generative topographic mapping.
SIAM Journal on Scientific Computing, 36(3):A1027-A1047, 2014.
Also available as INS Preprint No. 1311. [ bib | DOI | http | .pdf 1 ] |
[6] |
M. Griebel and A. Hullmann.
An efficient sparse grid Galerkin approach for the numerical
valuation of basket options under Kou's jump-diffusion model.
In Sparse grids and Applications, Lecture Notes in
Computational Science and Engineering, pages 121-150. Springer, 2013.
Also available as INS Preprint No. 1202. [ bib | .pdf 1 ] |
[7] |
A. Hullmann.
Schnelle Varianten des Generative Topographic Mapping.
Diplomarbeit, Institut für Numerische Simulation, Universität
Bonn, Dec. 2009. [ bib | .pdf 1 ] |