Research Group of Prof. Dr. M. Griebel
Institute for Numerical Simulation
maximize

Dr. Jens Oettershagen

Address: Institut für Numerische Simulation
Wegelerstr. 6
53115 Bonn
Germany
Office: We6 6.017
Phone: +49 228 733486
E-Mail: oettershagen.ins.uni-bonn.de

Former member of the institute

Now at Deutsche Post DHL (http://www.dpdhl.com)


Research Interests

with applications to



Research Projects

Project DFG GR 1144/21-1: Likelihood-Approximation für Discrete Choice Modelle
Cluster of Excellence: Hausdorff Center for Mathematics
Project Area J: High-dimensional problems and multi-scale methods

Completed Research Projects

Efficient enumeration of Frolov lattice points
DFG SFB 1060: The Mathematics of Emergent Effects
Project A07: A new sparse grid cumulant method for the electronic Schrödinger equation

Teaching


Theses (co-supervised)

[1] T. Ruland. Quadrature Approximation for Feature Maps in Kernel Methods. Masterarbeit, Institut für Numerische Simulation, Universität Bonn, 2017.
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[2] C. Kacwin. Realization of the Frolov cubature formula via orthogonal Chebyshev-Frolov lattices. Masterarbeit, Institut für Numerische Simulation, Universität Bonn, 2016.
bib | .pdf 1 ]
[3] F. Schildmann. Maximum-Likelihood-Approximation mit dünnen Gittern. Bachelorarbeit, Institut für Numerische Simulation, Universität Bonn, 2012.
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Publications

[1] G. Avila, J. Oettershagen, and T. Carrington. Comparing nested sequences of Leja and PseudoGauss points to interpolate in 1D and solve the Schroedinger equation in 9D. In Sparse grids and Applications, Lecture Notes in Computational Science and Engineering. Springer, 2018. To appear.
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[2] C. Kacwin, J. Oettershagen, M. Ullrich, and T. Ullrich. Numerical performance of optimized Frolov lattices in tensor product reproducing kernel Sobolev spaces. 2018. INS Preprint No. 1801.
bib | arXiv | .pdf 1 ]
[3] J. Oettershagen. On optimal quadrature in reproducing kernel Hilbert spaces. 2018. submitted.
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[4] J. Oettershagen. Construction of Optimal Cubature Algorithms with Applications to Econometrics and Uncertainty Quantification. Dissertation, Institut für Numerische Simulation, Universität Bonn, jan 2017.
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[5] C. Kacwin, J. Oettershagen, and T. Ullrich. On the orthogonality of the Chebyshev-Frolov lattice and applications. Monatshefte für Mathematik, 184(3):425–441, 2017.
bib | DOI | arXiv ]
[6] M. Griebel and J. Oettershagen. On tensor product approximation of analytic functions. Journal of Approximation Theory, 207:348-379, 2016. Also available as INS Preprint No. 1512.
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[7] A. Hinrichs, L. Markhasin, J. Oettershagen, and T. Ullrich. Optimal quasi-Monte Carlo rules on higher order digital nets for the numerical integration of multivariate periodic functions. Numerische Mathematik, 134(1):163-196, 2016.
bib | DOI | arXiv ]
[8] A. Hinrichs and J. Oettershagen. Optimal point sets for quasi-Monte Carlo integration of bivariate periodic functions with bounded mixed derivatives. In R. Cools and D. Nuyens, editors, Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April 2014, pages 385-405. Springer International Publishing, 2016.
bib | DOI | arXiv ]
[9] M. Griebel and J. Oettershagen. Dimension-adaptive sparse grid quadrature for integrals with boundary singularities. In Sparse grids and Applications, volume 97 of Lecture Notes in Computational Science and Engineering, pages 109-136. Springer, 2014. Also available as INS Preprint no 1310.
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[10] J. Oettershagen. Reduktion der effektiven Dimension und ihre Anwendung auf hochdimensionale Probleme. Diplomarbeit, Institut für Numerische Simulation, Universität Bonn, 2011.
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Talks

Conference contributions

[1] Optimal sparse grid integration in reproducing kernel Hilbert spaces with application to econometrics,
SGA16 - 4th Workshop on Sparse Grids and Applications, Miami, FL, USA, October 4-7, 2016.
[2] Higher order Monte Carlo integration,
MCQMC16 - 12th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing , Stanford, CA, USA, August 14-18, 2016.
[3] Tensor product approximation of multivariate analytic functions,
UQ16 - SIAM Conference on Uncertainty Quantification, Lausanne, Switzerland, April 5-8, 2016.
[4] Optimal integration of smooth functions with sparse grids,
SGA14 - 3rd Workshop on Sparse Grids and Applications, Stuttgart, Germany, September 1-5, 2014.
[5] Greedy construction of optimal sparse grid cubature formulas for smooth integrands,
MC-QMC2014 - Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, Leuven, Belgium, April 6-11, 2014.
[6] Sparse tensor products of optimal quadrature formulae,
HDA2013 - 5th Workshop on High-Dimensional Approximation, Canberra, Australia, February 11-15, 2013.
[7] Approximation of linear functionals in reproducing kernel Hilbert spaces,
Algorithms and Complexity for Continuous Problems, Schloss Dagstuhl, Wadern, Germany, September 23-28, 2012.
[8] Optimal approximation in reproducing kernel Hilbert spaces ,
DWCAA 2012 - 3rd Dolomites Workshop on Constructive Approximation and Applications, Alba di Canazei, Italy, September 9-14, 2012.
[9] Dimension-adaptive Sparse Grid Quadrature for Integrals with Boundary Singularities,
2nd Workshop on Sparse Grids and Applications, Munich, Germany, July 2-6, 2012.

Other Talks

[1] On the construction of optimal cubature rules with applications to uncertainty quantification,
Quasi-Monte Carlo Methods: Theory and Applications, Linz, Austria, June 7, 2017.
[2] Optimal integration in reproducing kernel Hilbert spaces,
Seminar Prof. Harbrecht, Basel, Switzerland, March 24, 2017.
[3] Optimal quadrature rules, nonlinear approximation and sparse tensor products,
Seminar for Analysis, Aachen, Germany, May 16, 2016.
[4] Optimal integration in reproducing kernel Hilbert spaces,
Seminar for Analysis, Linz, Austria, December 9, 2015.
[5] Multivariate integration with sparse grids,
SFB F55 Quasi-Monte Carlo methods: Theory and applications, Linz, Austria, May 12, 2014.
[6] Optimized pointsets for numerical integration,
Seminar on Mathematics of Computation, Bonn, Germany, February 3, 2014.