Born: October 1993 (age 25)
Profile on Google Scholar
Profile on ResearchGate
arXiv author page
Education
| since 06/2015 | PhD student at the Seminar for Applied Mathematics, ETH Zurich |
| 05/2015 | Master degree in Mathematics, ETH Zurich |
| 09/2014 | Bachelor degree in Mathematics, ETH Zurich |
| 08/2013-01/2014 | Term abroad at NUS (Singapore) |
| 08/2010 | Matura at the Mathematisch-Naturwissenschaftliches Gymnasium Rämibühl |
Preprints and publications
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Jentzen, A., Salimova, D., and Welti, T., A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients. [arXiv] (2018), 48 pages.
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Jentzen, A., Salimova, D., and Welti, T., Strong convergence for explicit space–time discrete numerical approximation methods for stochastic Burgers equations. J. Math. Anal. Appl. 469 (2019), no. 2, 661-704. [arXiv]
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Jacobe de Naurois, L., Jentzen, A., and Welti, T., Lower Bounds for Weak Approximation Errors for Spatial Spectral Galerkin Approximations of Stochastic Wave Equations. In: Stochastic Partial Differential Equations and Related Fields Springer International Publishing, Cham, 2018, 237-248. [arXiv]
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Andersson, A., Jentzen, A., Kurniawan, R., and Welti, T., On the differentiability of solutions of stochastic evolution equations with respect to their initial values. Nonlinear Anal. 162 (2017), 128-161. [arXiv]
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Cox, S., Hutzenthaler, M., Jentzen, A., van Neerven, J., and Welti, T., Convergence in Hölder norms with applications to Monte Carlo methods in infinite dimensions. [arXiv] (2016), 48 pages. To appear in IMA J. Num. Anal.
- Jacobe de Naurois, L., Jentzen, A., and Welti, T., Weak convergence rates for spatial spectral Galerkin approximations of semilinear stochastic wave equations with multiplicative noise. [arXiv] (2015), 27 pages. Accepted in Appl. Math. Optim.