| 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 | 99 | 2018 |
| Exponential ReLU DNN expression of holomorphic maps in high dimension JAA Opschoor, C Schwab, J Zech Constructive Approximation, 1-46, 2021 | 39 | 2021 |
| 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 | 32 | 2017 |
| 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 | 24 | 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 | 24 | 2018 |
| Convergence rates of high dimensional Smolyak quadrature J Zech, C Schwab ESAIM: Mathematical Modelling and Numerical Analysis 54 (4), 1259-1307, 2020 | 21 | 2020 |
| Deep neural network expression of posterior expectations in Bayesian PDE inversion L Herrmann, C Schwab, J Zech Inverse Problems 36 (12), 125011, 2020 | 19* | 2020 |
| 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 | 13 | 2020 |
| Sparse-grid approximation of high-dimensional parametric PDEs J Zech ETH Zurich, 2018 | 11* | 2018 |
| 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 | 8 | 2015 |
| Sparse approximation of triangular transports on bounded domains J Zech, Y Marzouk arXiv preprint arXiv:2006.06994, 2020 | 7 | 2020 |
| 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 |
| Deep learning in high dimension: ReLU network Expression Rates for Bayesian PDE inversion JAA Opschoor, C Schwab, J Zech SAM Research Report 2020, OSZ20_920, 2020 | 2 | 2020 |
| 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 |
| Numerical Methods for Bayesian Inverse Problems R Scheichl, J Zech | | 2021 |
| Sparse approximation of triangular transports. Part II: the infinite dimensional case J Zech, Y Marzouk arXiv preprint arXiv:2107.13422, 2021 | | 2021 |
| Domain uncertainty quantification in computational electromagnetics RD Aylwin Pincheira, CF Jerez Hanckes, C Schwab, J Zech | | 2020 |
| Sparse-Grid Approximation of High-Dimensional Parametric PDEs J Zech Dissertation 25683, ETH Zürich, http://dx. doi. org/10.3929/ethz-b-000340651, 2018 | | 2018 |
| 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 |
Christoph SchwabProfessor for Mathematics, ETH ZurichVerified email at math.ethz.ch
