photo Philippe von Wurstemberger
ETH Zurich

Address:
Philippe von Wurstemberger
RiskLab Switzerland / Group 3
Department of Mathematics
ETH Zurich
Rämistrasse 101
8092 Zürich
Switzerland

Office: Room HG G 47.1
Phone: +41 44 632 6966
Fax: +41 44 632 1104

E-mail: philippe.vonwurstemberger (at) math.ethz.ch

Links: [Curriculum Vitae] [Profile on ResearchGate] [Profile on GoogleScholar]
Last update of this homepage: June 4th, 2020

Education

2019 - PhD student in Mathematics at ETH Zurich under the supervision of Prof. Patrick Cheridito and Prof. Arnulf Jentzen
2018 - 2019 PhD student in Mathematics at ETH Zurich under the supervision of Prof. Arnulf Jentzen
2016 - 2018 Master of Science in Mathematics, ETH Zurich, Switzerland
2012 - 2015 Bachelor of Science in Mathematics, ETH Zurich, Switzerland

Publications

  • Jentzen, A., von Wurstemberger, P., Lower error bounds for the stochastic gradient descent optimization algorithm: Sharp convergence rates for slowly and fast decaying learning rates. Journal of Complexity 57 (2020). [arXiv].
  • Jentzen, A., Kuckuck, B., Neufeld, A., von Wurstemberger, P., Strong error analysis for stochastic gradient descent optimization algorithms. IMA J. Numer. Anal. (2020). [arXiv].

Preprints

  • Hutzenthaler, M., Jentzen, A., Kruse, T., Nguyen, T. A., von Wurstemberger, P., Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations. [arXiv] (2018), 27 pages.
  • Grohs, P., Hornung, F., Jentzen, A., von Wurstemberger, P., A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. [arXiv] (2018), 124 pages. To appear in the Memoires of the American Mathematical Society.
  • Hutzenthaler, M., Jentzen, A., von Wurstemberger, P., Overcoming the curse of dimensionality in the approximative pricing of financial derivatives with default risks. [arXiv] (2019), 71 pages. To appear in Electronic Journal of Probability.
  • Becker, S., Braunwarth, R., Hutzenthaler, M., Jentzen, A., von Wurstemberger, P., Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations. [arXiv] (2020), 21 pages.