12 citations · 20 across the 12 of their papers we have counts for
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Multilevel Domain Uncertainty Quantification in Computational Electromagnetics
Rubén Aylwin, Carlos Jerez-Hanckes, Christoph Schwab +1
We continue our study [Domain Uncertainty Quantification in Computational Electromagnetics, JUQ (2020), 8:301--341] of the numerical approximation of time-harmonic electromagnetic…
Neural and spectral operator surrogates: unified construction and expression rate bounds
Lukas Herrmann, Christoph Schwab, Jakob Zech
Approximation rates are analyzed for deep surrogates of maps between infinite-dimensional function spaces, arising e.g. as data-to-solution maps of linear and nonlinear partial dif…
Multilevel Optimization for Inverse Problems
Simon Weissmann, Ashia Wilson, Jakob Zech
Inverse problems occur in a variety of parameter identification tasks in engineering. Such problems are challenging in practice, as they require repeated evaluation of computationa…
De Rham compatible Deep Neural Network FEM
Marcello Longo, Joost A. A. Opschoor, Nico Disch +2
On general regular simplicial partitions of bounded polytopal domains , , we construct \emph{exact neural network (NN) emulations}…
Analyticity and sparsity in uncertainty quantification for PDEs with Gaussian random field inputs
Dinh Dũng, Van Kien Nguyen, Christoph Schwab +1
We establish sparsity and summability results for coefficient sequences of Wiener-Hermite polynomial chaos expansions of countably-parametric solutions of linear elliptic and parab…