| Deep learning in high dimension: Neural network expression rates for generalized polynomial chaos expansions in UQ C Schwab, J Zech Analysis and Applications, 1-37, 2018 | 54 | 2018 |
| Electromagnetic wave scattering by random surfaces: Shape holomorphy C Jerez-Hanckes, C Schwab, J Zech Mathematical Models and Methods in Applied Sciences 27 (12), 2229-2259, 2017 | 21 | 2017 |
| Convergence rates of high dimensional Smolyak quadrature J Zech, C Schwab ESAIM: Mathematical Modelling and Numerical Analysis 54 (4), 1259-1307, 2020 | 18 | 2020 |
| Multilevel approximation of parametric and stochastic PDEs J Zech, D Dũng, C Schwab Mathematical Models and Methods in Applied Sciences 29 (09), 1753-1817, 2019 | 18 | 2019 |
| Exponential ReLU DNN expression of holomorphic maps in high dimension JAA Opschoor, C Schwab, J Zech SAM Research Report 2019, 2019 | 16 | 2019 |
| Shape Holomorphy of the Stationary Navier--Stokes Equations A Cohen, C Schwab, J Zech SIAM Journal on Mathematical Analysis 50 (2), 1720-1752, 2018 | 12 | 2018 |
| Domain uncertainty quantification in computational electromagnetics R Aylwin, C Jerez-Hanckes, C Schwab, J Zech SIAM/ASA Journal on Uncertainty Quantification 8 (1), 301-341, 2020 | 7 | 2020 |
| Sparse-grid approximation of high-dimensional parametric PDEs J Zech ETH Zurich, 2018 | 7 | 2018 |
| Deep relu neural network expression rates for data-to-qoi maps in bayesian pde inversion L Herrmann, C Schwab, J Zech Technical Report 2020-02, Seminar for Applied Mathematics, ETH Zürich …, 2020 | 6 | 2020 |
| Deep learning in high dimension C Schwab, J Zech preprint, 2017 | 5 | 2017 |
| A Posteriori Error Estimation of - Finite Element Methods for Highly Indefinite Helmholtz Problems S Sauter, J Zech SIAM Journal on Numerical Analysis 53 (5), 2414-2440, 2015 | 4 | 2015 |
| Uncertainty quantification for spectral fractional diffusion: Sparsity analysis of parametric solutions L Herrmann, C Schwab, J Zech SIAM/ASA Journal on Uncertainty Quantification 7 (3), 913-947, 2019 | 3 | 2019 |
| Shape holomorphy of the stationary Navier-Stokes equations A Cohen, C Schwab, J Zech | 3 | 2016 |
| A posteriori error estimation of hp-DG finite element methods for highly indefinite Helmholtz problems J Zech master’s thesis, Inst. f. Mathematik, Unversität Zürich, 2014. http://www …, 2014 | 2 | 2014 |
| Deep learning in high dimension: ReLU network Expression Rates for Bayesian PDE inversion JAA Opschoor, C Schwab, J Zech | | 2020 |
| Sparse approximation of triangular transports on bounded domains J Zech, Y Marzouk arXiv preprint arXiv:2006.06994, 2020 | | 2020 |
| High dimensional Smolyak quadrature J Zech NumPDE Summer Retreat, Disentis, Switzerland, 2017 | | 2017 |
| Shape holomorphy of the stationary Stokes and Navier-Stokes equation J Zech 14th European Finite Element Fair, 2016 | | 2016 |
| Domain Uncertainty for Navier Stokes Equations J Zech SIAM Conference on Uncertainty Quantification (UQ 2016), 2016 | | 2016 |
| Nonlinear n-term approximation for the solution of the dirichlet problem M Hansen, C Schwab, J Zech | | 2013 |
Christoph SchwabProfessor for Mathematics, ETH ZurichVerified email at math.ethz.ch
