| Deep ReLU networks and high-order finite element methods JAA Opschoor, PC Petersen, C Schwab Analysis and Applications 18 (05), 715-770, 2020 | 141 | 2020 |
| Exponential ReLU DNN expression of holomorphic maps in high dimension JAA Opschoor, C Schwab, J Zech Constructive Approximation 55 (1), 537-582, 2022 | 110 | 2022 |
| Exponential ReLU neural network approximation rates for point and edge singularities C Marcati, JAA Opschoor, PC Petersen, C Schwab Foundations of Computational Mathematics 23 (3), 1043-1127, 2023 | 28 | 2023 |
| Constructive deep ReLU neural network approximation L Herrmann, JAA Opschoor, C Schwab Journal of Scientific Computing 90 (2), 75, 2022 | 28 | 2022 |
| Deep learning in high dimension: ReLU network expression rates for bayesian PDE inversion JAA Opschoor, C Schwab, J Zech SAM Research Report 2020, 2020 | 11 | 2020 |
| De Rham compatible Deep Neural Network FEM M Longo, JAA Opschoor, N Disch, C Schwab, J Zech arXiv preprint arXiv:2201.05395, 2022 | 9 | 2022 |
| De Rham compatible deep neural network FEM M Longo, JAA Opschoor, N Disch, C Schwab, J Zech Neural Networks 165, 721-739, 2023 | 7 | 2023 |
| Deep learning in high dimension: ReLU neural network expression for Bayesian PDE inversion JAA Opschoor, C Schwab, J Zech Optimization and Control for Partial Differential Equations: Uncertainty …, 2022 | 6 | 2022 |
| Deep ReLU networks and high-order finite element methods II: Chebyshev emulation JAA Opschoor, C Schwab arXiv preprint arXiv:2310.07261, 2023 | 4 | 2023 |
| Constructive deep neural network approximations of weighted analytic solutions to partial differential equations in polygons JAA Opschoor ETH Zurich, 2023 | 3 | 2023 |
| Neural Networks for Singular Perturbations JAA Opschoor, C Schwab, C Xenophontos arXiv preprint arXiv:2401.06656, 2024 | 2 | 2024 |
| Exponential Expressivity of ReLU Neural Networks on Gevrey Classes with Point Singularities JAA Opschoor, C Schwab arXiv preprint arXiv:2403.02035, 2024 | | 2024 |
| Deep learning in high dimension: ReLU neural network expression for Bayesian PDE inversion (extended version) JAA Opschoor, C Schwab, J Zech | | 2020 |
| Neural Networks for Singularly Perturbed Problems JAA Opschoor, C Schwab, C Xenophontos BOOK OF ABSTRACTS, 12, 0 | | |
| ReLU DNN expression of sparse gpc expansion in uncertainty quantification JAA Opschoor, C Schwab | | |
| Exponential Deep Neural Network Expression for Solution Sets of PDEs Christoph Schwab Seminar for Applied Mathematics ETH Zürich, Switzerland J Opschoor, CM ETH, L Gonon, L Herrmann, P Petersen, J Zech | | |
