Lukas Herrmann

发表

Deep neural network approximation for high-dimensional elliptic PDEs with boundary conditions pdf

Philipp Grohs, Lukas Herrmann, 2020, ArXiv.

Multilevel approximation of Gaussian random fields: Fast simulation

Christoph Schwab, Lukas Herrmann, Kristin Kirchner, 2019 .

Deep ReLU Neural Network Expression Rates for Data-to-QoI Maps in Bayesian PDE Inversion

Christoph Schwab, Lukas Herrmann, Jakob Zech, 2020 .

Uncertainty Quantification for Spectral Fractional Diffusion: Sparsity Analysis of Parametric Solutions

Christoph Schwab, Lukas Herrmann, Jakob Zech, 2019, SIAM/ASA J. Uncertain. Quantification.

Development of a Dynamic Electronic Speed Controller for Multicopters

Tobias Bruckmann, Dieter Schramm, Lukas Herrmann, 2019, 2019 18th European Control Conference (ECC).

Quasi-Monte Carlo Bayesian estimation under Besov priors in elliptic inverse problems

Lukas Herrmann, Christoph Schwab, Magdalena Keller, 2021, Math. Comput..

Deep neural network approximation for high-dimensional parabolic Hamilton-Jacobi-Bellman equations pdf

Philipp Grohs, Lukas Herrmann, P. Grohs, 2021, ArXiv.

Multilevel approximation of Gaussian random fields: Covariance compression, estimation and spatial prediction pdf

Helmut Harbrecht, Christoph Schwab, Lukas Herrmann, 2021, ArXiv.

Constructive Deep ReLU Neural Network Approximation

Christoph Schwab, Lukas Herrmann, Joost A. A. Opschoor, 2022, Journal of Scientific Computing.

QMC Algorithms with Product Weights for Lognormal-Parametric, Elliptic PDEs

Christoph Schwab, Lukas Herrmann, 2016 .