About Sören Wolfers Sören Wolfers Ph.D., Applied Mathematics and Computational Science numerical analysis uncertainty quantification Sören Wolfers obtained a Ph.D. degree in Applied Mathematics and Computational Sciences under the supervision of Professor Raul F. Tempone's at Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Sören's research interests included Numerical Analysis, Uncertainty Quantification, Sparse Approximation, Multilevel methods and Meshfree methods. Selected Publications Beck, J., Roberts, G., and Wolfers, S. (2018). Bayesian earthquake dating and seismic hazard assessment using chlorine-36 measurements (BED v1). Submitted to Articles Related News June 2020 Manuscript entitled "Pricing American options by exercise rate optimization" accepted in Quantitative Finance, and will be run as a feature 1 min read · Mon, Jun 22 2020 News The manuscript entitled "Pricing American options by exercise rate optimization" is accepted in Quantitative Finance, and will be run as a feature. The manuscript is authored by Christian Bayer, Raul Tempone, and Soren Wolfers. February 2019 Soren Wolfers succesfully defended his PhD Thesis 2 min read · Thu, Feb 7 2019 News In the field of uncertainty quantification, the effects of parameter uncertainties on scientific simulations may be studied by integrating or approximating a quantity of interest as a function over the parameter space. If this is done numerically, using regular grids with a fixed resolution, the required computational work increases exponentially with respect to the number of uncertain parameters - a phenomenon known as the curse of dimensionality. October 2018 Prof. Raul Tempone will participate in a Humboldt colloquium Buenos Aires, Argentina 1 min read · Thu, Oct 25 2018 News Prof. Raul Tempone will participate in a Humboldt colloquium (Buenos Aires, Argentina), presenting his KAUST work developed with the KAUST Ph.D. student Soeren Wolfers "Stochastic Control for multivariate American Options". February 2017 Alexander Litvinenko, Sören Wolfers, and Joakim Beck to present their work at the 7th Workshop on High-Dimensional Approximation 1 min read · Mon, Feb 13 2017 News Alexander Litvinenko, Sören Wolfers, and Joakim Beck will present their work at the 7th Workshop on High-Dimensional Approximation, February 13 – 17, 2017, The University of New South Wales, Sydney, Australia. October 2016 Prof. Raul Tempone is a plenary speaker at the 4th Workshop on Sparse Grids and Applications, October 4-7, 2016, Miami, Florida 1 min read · Fri, Oct 7 2016 News Prof. Raul Tempone is a plenary speaker at the 4th Workshop on Sparse Grids and Applications, October 4-7, 2016, Miami, Florida. September 2016 On Sep. 26th, 2016, PhD Candidate Sören Wolfers presented his Proposal Thesis Defense entitled "Sparse methods for the numerical approximation of parametric PDE" 1 min read · Mon, Sep 26 2016 News We study the numerical approximation of partial differential equations (PDEs) that depend on a parameter describing uncertain properties of the physical system under consideration. We exploit the algebraic structure of these problems to propose sparse, decomposition-based, algorithms that are able to lift this curse by combining a multilevel approach for the solution of the PDE with sparse grids for the parameter domain in a joint framework. Sparse approximation of multilinear problems with applications to kernel-based methods in UQ 1 min read · Thu, Sep 1 2016 News Sparse approximation We provide a framework for the sparse approximation of multilinear problems and show that several problems in uncertainty quantification fit within this framework. In these problems, the value of a multilinear map has to be approximated using approximations of different accuracy and computational work of the arguments of this map. September 2015 Seminar: Chebyshev nodes in multiple dimensions by PhD candidate Sören Wolfers 1 min read · Thu, Sep 10 2015 News Chebyshev nodes are well-known for their near-optimal polynomial interpolation and quadrature properties on intervals. In particular, the associated Lebesgue constant grows only logarithmically, whereas that associated with equispaced nodes grows exponentially. Generalizations of Chebyshev nodes to domains in multiple dimensions have previously been studied on hyper-cubes only. In this talk, we consider more general domains and study the properties of node sets that are similar to Chebyshev nodes in the sense that they are distributed more densely near the boundary of the domain.
Manuscript entitled "Pricing American options by exercise rate optimization" accepted in Quantitative Finance, and will be run as a feature 1 min read · Mon, Jun 22 2020 News The manuscript entitled "Pricing American options by exercise rate optimization" is accepted in Quantitative Finance, and will be run as a feature. The manuscript is authored by Christian Bayer, Raul Tempone, and Soren Wolfers.
Soren Wolfers succesfully defended his PhD Thesis 2 min read · Thu, Feb 7 2019 News In the field of uncertainty quantification, the effects of parameter uncertainties on scientific simulations may be studied by integrating or approximating a quantity of interest as a function over the parameter space. If this is done numerically, using regular grids with a fixed resolution, the required computational work increases exponentially with respect to the number of uncertain parameters - a phenomenon known as the curse of dimensionality.
Prof. Raul Tempone will participate in a Humboldt colloquium Buenos Aires, Argentina 1 min read · Thu, Oct 25 2018 News Prof. Raul Tempone will participate in a Humboldt colloquium (Buenos Aires, Argentina), presenting his KAUST work developed with the KAUST Ph.D. student Soeren Wolfers "Stochastic Control for multivariate American Options".
Alexander Litvinenko, Sören Wolfers, and Joakim Beck to present their work at the 7th Workshop on High-Dimensional Approximation 1 min read · Mon, Feb 13 2017 News Alexander Litvinenko, Sören Wolfers, and Joakim Beck will present their work at the 7th Workshop on High-Dimensional Approximation, February 13 – 17, 2017, The University of New South Wales, Sydney, Australia.
Prof. Raul Tempone is a plenary speaker at the 4th Workshop on Sparse Grids and Applications, October 4-7, 2016, Miami, Florida 1 min read · Fri, Oct 7 2016 News Prof. Raul Tempone is a plenary speaker at the 4th Workshop on Sparse Grids and Applications, October 4-7, 2016, Miami, Florida.
On Sep. 26th, 2016, PhD Candidate Sören Wolfers presented his Proposal Thesis Defense entitled "Sparse methods for the numerical approximation of parametric PDE" 1 min read · Mon, Sep 26 2016 News We study the numerical approximation of partial differential equations (PDEs) that depend on a parameter describing uncertain properties of the physical system under consideration. We exploit the algebraic structure of these problems to propose sparse, decomposition-based, algorithms that are able to lift this curse by combining a multilevel approach for the solution of the PDE with sparse grids for the parameter domain in a joint framework.
Sparse approximation of multilinear problems with applications to kernel-based methods in UQ 1 min read · Thu, Sep 1 2016 News Sparse approximation We provide a framework for the sparse approximation of multilinear problems and show that several problems in uncertainty quantification fit within this framework. In these problems, the value of a multilinear map has to be approximated using approximations of different accuracy and computational work of the arguments of this map.
Seminar: Chebyshev nodes in multiple dimensions by PhD candidate Sören Wolfers 1 min read · Thu, Sep 10 2015 News Chebyshev nodes are well-known for their near-optimal polynomial interpolation and quadrature properties on intervals. In particular, the associated Lebesgue constant grows only logarithmically, whereas that associated with equispaced nodes grows exponentially. Generalizations of Chebyshev nodes to domains in multiple dimensions have previously been studied on hyper-cubes only. In this talk, we consider more general domains and study the properties of node sets that are similar to Chebyshev nodes in the sense that they are distributed more densely near the boundary of the domain.
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