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Staff Dr. Jens Oettershagen

Mr. Oettershagen is now at Deutsche Post DHL. This page is no longer maintained.

Contact Information

E-Mail: ed tod nnob-inu tod sni ta negahsretteoa tod b@foo tod de

Research Interests

  • Complexity of high-dimensional problems and tractability
  • Kernel methods
  • (Quasi-)Monte Carlo methods
  • Sparse grids
  • (Global) optimization

with applications to

  • Econometrics
  • Computational finance
  • Machine learning
  • Quantum mechanics


Winter semester 2017/18

See teaching activities of the whole group.

Completed Research Projects

Efficient enumeration of Frolov lattice points



Theses (co-supervised)

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


  1. Sparse tensor product approximation for a class of generalized method of moments estimators. A. Gilch, M. Griebel, and J. Oettershagen. International Journal for Uncertainty Quantification, 12(2):53–79, 2022. Also available as INS Preprint No. 2006. BibTeX PDF DOI
  2. Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids. B. Bohn, M. Griebel, and J. Oettershagen. In Proceedings of the 2019 SIAM International Conference on Data Mining, 163–171. 2019. Also available as INS Preprint No. 1812. BibTeX PDF DOI
  3. Maximum approximated likelihood estimation. M. Griebel, F. Heiss, J. Oettershagen, and C. Weiser. Submitted to Econometric Theory. Available as INS Preprint No. 1905, 2019. BibTeX PDF
  4. Comparing nested sequences of Leja and PseudoGauss points to interpolate in 1D and solve the Schroedinger equation in 9D. G. Avila, J. Oettershagen, and T. Carrington. In Sparse grids and Applications, Lecture Notes in Computational Science and Engineering. Springer, 2018. BibTeX
  5. Numerical performance of optimized Frolov lattices in tensor product reproducing kernel Sobolev spaces. C. Kacwin, J. Oettershagen, M. Ullrich, and T. Ullrich. Preprint Uni Bonn, pages 1–40, 2018. INS Preprint No. 1801. BibTeX PDF
  6. On the orthogonality of the Chebyshev-Frolov lattice and applications. C. Kacwin, J. Oettershagen, and T. Ullrich. Monatshefte für Mathematik, 184(3):425–441, 2017. BibTeX DOI arXiv
  7. Construction of Optimal Cubature Algorithms with Applications to Econometrics and Uncertainty Quantification. J. Oettershagen. Dissertation, Institut für Numerische Simulation, Universität Bonn, 2017. BibTeX PDF
  8. On tensor product approximation of analytic functions. M. Griebel and J. Oettershagen. Journal of Approximation Theory, 207:348–379, 2016. Also available as INS Preprint No. 1512. BibTeX PDF
  9. Optimal quasi-Monte Carlo rules on higher order digital nets for the numerical integration of multivariate periodic functions. A. Hinrichs, L. Markhasin, J. Oettershagen, and T. Ullrich. Numerische Mathematik, 134(1):163–196, 2016. BibTeX DOI arXiv
  10. Optimal point sets for quasi-Monte Carlo integration of bivariate periodic functions with bounded mixed derivatives. A. Hinrichs and J. Oettershagen. 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. BibTeX DOI arXiv
  11. Dimension-adaptive sparse grid quadrature for integrals with boundary singularities. M. Griebel and J. Oettershagen. In Sparse grids and Applications, volume 97 of Lecture Notes in Computational Science and Engineering, pages 109–136. Springer, 2014. BibTeX PDF
  12. Reduktion der effektiven Dimension und ihre Anwendung auf hochdimensionale Probleme. J. Oettershagen. Diplomarbeit, Institut für Numerische Simulation, Universität Bonn, 2011. BibTeX PDF