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Jakob Zech
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2020 – today
- 2024
- [i13]Simon Weissmann, Jakob Zech:
On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation. CoRR abs/2402.01320 (2024) - 2023
- [j6]Christoph Schwab, Jakob Zech:
Deep Learning in High Dimension: Neural Network Expression Rates for Analytic Functions in \(\pmb{L^2(\mathbb{R}^d,\gamma_d)}\). SIAM/ASA J. Uncertain. Quantification 11(1): 199-234 (2023) - [j5]Marcello Longo, Joost A. A. Opschoor, Nico Disch, Christoph Schwab, Jakob Zech:
De Rham compatible Deep Neural Network FEM. Neural Networks 165: 721-739 (2023) - [i12]Christoph Schwab, Andreas Stein, Jakob Zech:
Deep Operator Network Approximation Rates for Lipschitz Operators. CoRR abs/2307.09835 (2023) - [i11]Youssef M. Marzouk, Zhi Ren, Sven Wang, Jakob Zech:
Distribution learning via neural differential equations: a nonparametric statistical perspective. CoRR abs/2309.01043 (2023) - [i10]Josephine Westermann, Jakob Zech:
Measure transport via polynomial density surrogates. CoRR abs/2311.04172 (2023) - [i9]Björn Sprungk, Simon Weissmann, Jakob Zech:
Metropolis-adjusted interacting particle sampling. CoRR abs/2312.13889 (2023) - 2022
- [c1]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. COLT 2022: 5489-5524 - [i8]Dinh Dung, Van Kien Nguyen, Christoph Schwab, Jakob Zech:
Analyticity and sparsity in uncertainty quantification for PDEs with Gaussian random field inputs. CoRR abs/2201.01912 (2022) - [i7]Marcello Longo, Joost A. A. Opschoor, Nico Disch, Christoph Schwab, Jakob Zech:
De Rham compatible Deep Neural Networks. CoRR abs/2201.05395 (2022) - [i6]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. CoRR abs/2204.13732 (2022) - [i5]Lukas Herrmann, Christoph Schwab, Jakob Zech:
Neural and gpc operator surrogates: construction and expression rate bounds. CoRR abs/2207.04950 (2022) - [i4]Rubén Aylwin, Carlos Jerez-Hanckes, Christoph Schwab, Jakob Zech:
Multilevel Domain Uncertainty Quantification in Computational Electromagnetics. CoRR abs/2212.07240 (2022) - 2021
- [i3]Jakob Zech, Youssef M. Marzouk:
Sparse approximation of triangular transports. Part II: the infinite dimensional case. CoRR abs/2107.13422 (2021) - [i2]Christoph Schwab, Jakob Zech:
Deep Learning in High Dimension: Neural Network Approximation of Analytic Functions in L2(Rd, γd). CoRR abs/2111.07080 (2021) - 2020
- [j4]Rubén Aylwin, Carlos Jerez-Hanckes, Christoph Schwab, Jakob Zech:
Domain Uncertainty Quantification in Computational Electromagnetics. SIAM/ASA J. Uncertain. Quantification 8(1): 301-341 (2020) - [i1]Jakob Zech, Youssef M. Marzouk:
Sparse approximation of triangular transports on bounded domains. CoRR abs/2006.06994 (2020)
2010 – 2019
- 2019
- [j3]Lukas Herrmann, Christoph Schwab, Jakob Zech:
Uncertainty Quantification for Spectral Fractional Diffusion: Sparsity Analysis of Parametric Solutions. SIAM/ASA J. Uncertain. Quantification 7(3): 913-947 (2019) - 2018
- [j2]Albert Cohen, Christoph Schwab, Jakob Zech:
Shape Holomorphy of the Stationary Navier-Stokes Equations. SIAM J. Math. Anal. 50(2): 1720-1752 (2018) - 2015
- [j1]Stefan A. Sauter, Jakob Zech:
A Posteriori Error Estimation of hp-dG Finite Element Methods for Highly Indefinite Helmholtz Problems. SIAM J. Numer. Anal. 53(5): 2414-2440 (2015)
Coauthor Index
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last updated on 2024-04-25 02:01 CEST by the dblp team
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