Timo Welti
Timo Welti
Bestätigte E-Mail-Adresse bei sam.math.ethz.ch - Startseite
Zitiert von
Zitiert von
A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant …
A Jentzen, D Salimova, T Welti
arXiv preprint arXiv:1809.07321, 2018
Solving high-dimensional optimal stopping problems using deep learning
S Becker, P Cheridito, A Jentzen, T Welti
arXiv preprint arXiv:1908.01602, 2019
Convergence in Hölder norms with applications to Monte Carlo methods in infinite dimensions
S Cox, M Hutzenthaler, A Jentzen, J van Neerven, T Welti
IMA Journal of Numerical Analysis, 2016
Strong convergence for explicit space–time discrete numerical approximation methods for stochastic Burgers equations
A Jentzen, D Salimova, T Welti
Journal of Mathematical Analysis and Applications 469 (2), 661-704, 2019
Weak convergence rates for spatial spectral Galerkin approximations of semilinear stochastic wave equations with multiplicative noise
LJ de Naurois, A Jentzen, T Welti
arXiv preprint arXiv:1508.05168, 2015
Generalised multilevel Picard approximations
MB Giles, A Jentzen, T Welti
arXiv preprint arXiv:1911.03188, 2019
On the differentiability of solutions of stochastic evolution equations with respect to their initial values
A Andersson, A Jentzen, R Kurniawan, T Welti
Nonlinear Analysis 162, 128-161, 2017
Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation
A Jentzen, T Welti
arXiv preprint arXiv:2003.01291, 2020
Lower bounds for weak approximation errors for spatial spectral Galerkin approximations of stochastic wave equations
LJ de Naurois, A Jentzen, T Welti
International Conference on Stochastic Partial Differential Equations and …, 2016
High-dimensional Stochastic Approximation: Algorithms and Convergence Rates
T Welti
ETH Zurich, 2020
On approximation algorithms for stochastic ordinary differential equations (SDEs) and stochastic partial differential equations (SPDEs)
A Jentzen, G Da Prato, E Weinan, M Gerencsér, M Hairer, M Hefter, ...
Workshop on Infinite Dimensional Probability, King's College London, 2017
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