Leiter der Arbeitsgruppe
Jun.-Prof. Dr. rer. nat. Björn Sprungk
Juniorprofessor für Angewandte Mathematik
Universitätshauptgebäude, Prüferstr. 9, Zimmer DG.02
Telefon +49 3731 39-3225
Fax +49 3731 39-3442
bjoern [dot] sprungk
math [dot] tu-freiberg [dot] de
Kurze Vita
| Zeitraum | Tätigkeit |
|---|---|
| seit 02/2020 | Tenure-Track Professor für Angewandte Mathematik an der Fakultät für Mathematik und Informatik der TU Bergakademie Freiberg |
| 04/2018 - 01/2020 | Postdoc am Institut für Mathematische Stochastik der Georg-August Universität Göttingen |
| 08/2017 - 03/2018 | Postdoc im DFG-Graduiertenkolleg 1953 "Statistical Modeling of Complex Systems and Processes" an der Universität Mannheim |
| 06/2017 | Promotion (Dr. rer. nat.) über "Numerical Methods for Bayesian Inference in Hilbert Spaces" an der TU Chemnitz |
| 05/2013 - 08/2017 | Wissenschaftlicher Mitarbeiter und Doktorand an der Professur Numerische Mathematik der TU Chemnitz |
| 04/2011 - 04/2013 | Wissenschaftlicher Mitarbeiter am Institut für Numerische Mathematik und Optimierung der TU Bergakademie Freiberg im Rahmen des DFG-Schwerpunktprogramms 1324 "Extraktion quantifizierbarer Information aus komplexen Systemen" |
| 07/2009 - 12/2009 | Auslandssemester an der Technisch-Naturwissenschaftlichen Universität Norwegens in Trondheim |
| 10/2005 - 03/2011 | Diplomstudium der Angewandten Mathematik an der TU Bergakademie Freiberg |
| 1985 | Geboren in Possendorf (Sachsen) |
Aktuelle Lehre
Forschung und Publikationen
Forschungsinteressen
- Unsicherheitsquantifizierung für Differentialgleichungen
- Hochdimensionale Approximationsmethoden
- Monte-Carlo-Verfahren
- Theorie der Markowschen Ketten
- Bayessche Inferenz
- Inverse Probleme
Preprints
- Hasenpflug, M., Rudolf, D., Sprungk, B. (2022)
Wasserstein convergence rates of increasingly concentrating probability measures
arXiv:2207.08551, 1-36. - Rudolf, D., Sprungk, B. (2022)
Robust random walk-like Metropolis-Hastings algorithms for concentrating posteriors.
arXiv:2202.12127, 1-27. - Lie, H. C., Rudolf, D., Sprungk, B., Sullivan T. J. (2021)
Dimension-independent Markov chain Monte Carlo on the sphere.
arXiv:2112.12185, 1-35.
Begutachtete Publikationen
- Ernst, O. G., Pichler, A., Sprungk, B. (2022).
Wasserstein sensitivity of Risk and Uncertainty Propagation.
SIAM/ASA J. Uncertainty Quantification 10(3), 915-948. [arXiv]. - Eigel, M., Ernst, O., Sprungk, B., Tamellini, L. (2022)
On the convergence of adaptive stochastic collocation for elliptic partial differential equations with affine diffusion.
SIAM J. Numer. Anal. 60(2), 659-687 [arXiv] - Ernst, O. G., Sprungk, B., Tamellini, L. (2022).
On Expansions and Nodes for Sparse Grid Collocation of Lognormal Elliptic PDEs.
In: H.-J. Bungartz et al. (Hrsg.) Sparse Grids and Applications - Munich 2018, Lecture Notes in Computational Science and Engineering, Band 144, Springer, Cham, pp. 1-31. [arXiv] - Natarovskii, V., Rudolf, D., Sprungk, B. (2021)
Geometric convergence of elliptical slice sampling.
Proceedings of the 38th International Conference on Machine Learning, PLMR 139, 7969-7978 [arXiv] - Klebanov, I., Sprungk, B., Sullivan, T. J. (2021)
The linear conditional expectation in Hilbert space.
Bernoulli 27(4), 2267-2299. [arXiv] - Natarovskii, V., Rudolf, D., Sprungk, B. (2021)
Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling.
Ann. Appl. Probab. 31 (2), 806-825. [arXiv] - Habeck, M., Rudolf, D., Sprungk, B. (2020)
Stability of doubly-intractable distributions.
Electron. Commun. Probab. 25, paper no. 62, 13 pp. [arXiv] - Schillings, C., Sprungk, B., Wacker, P. (2020)
On the Convergence of the Laplace Approximation and Noise-Level-Robustness of Laplace-based Monte Carlo Methods for Bayesian Inverse Problems.
Numerische Mathematik 145, 915-971. [arXiv] - Rudolf, D., Sprungk, B. (2020)
On a Metropolis-Hastings importance sampling estimator
Electron. J. Statist. 14(1), 857-889. [arXiv] - Sprungk, B. (2020)
On the Local Lipschitz Robustness of Bayesian Inverse Problems.
Inverse Problems 36 055015 (31pp). [arXiv] - Ernst, O. G., Sprungk, B., Tamellini, L. (2018)
Convergence of Sparse Collocation for Functions of Countably Many Gaussian Random Variables.
SIAM J. Numer. Anal. 56(2), 877-905. [arXiv] - Rudolf, D., Sprungk, B. (2018)
On a Generalization of the Preconditioned Crank-Nicolson Metropolis Algorithm.
Found. Comput. Math. 18, 309-343. [arXiv] - Rudolf, D., Sprungk, B. (2017)
Metropolis-Hastings Importance Sampling Estimator.
Proc. Appl. Math. Mech. 17, 731-734. - Hundt, S., Sprungk, B., Horsch, A. (2017)
The Information Content of Credit Ratings: Evidence from European Convertible Bond Markets.
The European Journal of Finance 23(14) , 1414-1445. - Ernst, O. G., Sprungk, B., Starkloff, H.-J. (2015)
Analysis of the ensemble and polynomial chaos Kalman filters in Bayesian inverse problems.
SIAM/ASA J. Uncertainty Quantification 3(1) , 823-851. [arXiv] - Ernst, O. G., Sprungk, B., Starkloff, H.-J. (2014)
Bayesian inverse problems and Kalman filters.
In: Dahlke S. et al. (Hrsg.) Extraction of Quantifiable Information from Complex Systems, Lecture Notes in Computational Science and Engineering, Band 102, Springer, Cham, pp. 133-159. - Ernst, O. G., Sprungk, B. (2014)
Stochastic collocation for elliptic PDEs with random data - the lognormal case.
In: J. Garcke und D. Pflüger (Hrsg.) Sparse Grids and Applications - Munich 2012, Lecture Notes in Computational Science and Engineering, Band 97, Springer, Cham, pp. 29-53. - Sprungk, B., van den Boogaart, K. G. (2013)
Stochastic differential equations with fuzzy drift and diffusion.
Fuzzy Sets and Systems 230(1), 53-64.
Thesen
- Sprungk, B. (2017)
Numerical Methods for Bayesian Inference in Hilbert Spaces.
Dissertation, TU Chemnitz. - Sprungk, B. (2011)
Fuzzy Stochastische Differentialgleichungen.
Diplomarbeit, TU Bergakademie Freiberg.