Lukas Herrmann
Lukas Herrmann
Johann Radon Institute for Computational and Applied Mathematics, RICAM
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
Deep neural network approximation for high-dimensional elliptic PDEs with boundary conditions
P Grohs, L Herrmann
IMA Journal of Numerical Analysis 42 (3), 2055-2082, 2022
Quasi--Monte Carlo integration for affine-parametric, elliptic PDEs: Local supports and product weights
RN Gantner, L Herrmann, C Schwab
SIAM Journal on Numerical Analysis 56 (1), 111-135, 2018
Deep neural network expression of posterior expectations in Bayesian PDE inversion
L Herrmann, C Schwab, J Zech
Inverse Problems 36 (12), 125011, 2020
Constructive deep ReLU neural network approximation
L Herrmann, JAA Opschoor, C Schwab
Journal of Scientific Computing 90 (2), 75, 2022
Multilevel quasi-Monte Carlo integration with product weights for elliptic PDEs with lognormal coefficients
L Herrmann, C Schwab
ESAIM: Mathematical Modelling and Numerical Analysis 53 (5), 1507-1552, 2019
QMC integration for lognormal-parametric, elliptic PDEs: local supports and product weights
L Herrmann, C Schwab
Numerische Mathematik 141, 63-102, 2019
Multilevel approximation of Gaussian random fields: Fast simulation
L Herrmann, K Kirchner, C Schwab
Mathematical Models and Methods in Applied Sciences 30 (1), 181-223, 2020
Numerical analysis of lognormal diffusions on the sphere
L Herrmann, A Lang, C Schwab
Stochastics and Partial Differential Equations: Analysis and Computations 6 …, 2018
Quasi-Monte Carlo Bayesian estimation under Besov priors in elliptic inverse problems
L Herrmann, M Keller, C Schwab
Mathematics of Computation 90 (330), 1831-1860, 2021
Multilevel QMC with product weights for affine-parametric, elliptic PDEs
RN Gantner, L Herrmann, C Schwab
Contemporary Computational Mathematics-a celebration of the 80th birthday of …, 2018
Neural and gpc operator surrogates: construction and expression rate bounds
L Herrmann, C Schwab, J Zech
arXiv preprint arXiv:2207.04950, 2022
Multilevel quasi-Monte Carlo uncertainty quantification for advection-diffusion-reaction
L Herrmann, C Schwab
International Conference on Monte Carlo and Quasi-Monte Carlo Methods in …, 2018
Deep neural network approximation for high-dimensional parabolic Hamilton-Jacobi-Bellman equations
P Grohs, L Herrmann
arXiv preprint arXiv:2103.05744, 2021
Multilevel approximation of Gaussian random fields: Covariance compression, estimation and spatial prediction
H Harbrecht, L Herrmann, K Kirchner, C Schwab
arXiv preprint arXiv:2103.04424, 2021
Strong convergence analysis of iterative solvers for random operator equations
L Herrmann
Calcolo 56 (4), 46, 2019
QMC algorithms with product weights for lognormal-parametric, elliptic PDEs
L Herrmann, C Schwab
Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2016, Stanford, CA, August …, 2018
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
Quasi-Monte Carlo integration in uncertainty quantification for PDEs with log-Gaussian random field inputs
L Herrmann
ETH Zurich, 2019
Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data
G Schneckenreither, L Herrmann, R Reisenhofer, N Popper, P Grohs
Plos one 18 (5), e0286012, 2023
Isotropic random fields on the sphere–stochastic heat equation and regularity of random elliptic PDEs
L Herrmann
Master's thesis, ETH Zürich, 2013
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