Peer Reviewed Journal Publication

  • Dick, J.; Ebert, A.; Herrmann, L.; Kritzer, P.; Longo, M. (online: 2023) The fast reduced QMC matrix-vector product. Journal of Computational and Applied Mathematics, Bd. 440, S. 115642.
    RIS ENW BIB
  • Abdeljawad, Ahmed; Grohs, Philipp (2022) Integral representations of shallow neural network with rectified power unit activation function. Neural Netw., Bd. 155, S. 536-550.
    DOI RIS ENW BIB
  • Grohs, Philipp; Rathmair, Martin (2022) Stable Gabor phase retrieval for multivariate functions. J. Eur. Math. Soc., Bd. 24 (5), S. 1593-1615.
    DOI RIS ENW BIB
  • Abdeljawad, Ahmed; Grohs, Philipp (2022) Approximations with deep neural networks in Sobolev time-space. Anal. Appl., Bd. 20 (03), S. 499-541.
    DOI RIS ENW BIB
  • Scherbela, Michael; Reisenhofer, Rafael; Gerard, Leon; Marquetand, Philipp; Grohs, Philipp (2022) Solving the electronic Schrodinger equation for multiple nuclear geometries with weight-sharing deep neural networks. NATURE COMPUTATIONAL SCIENCE, Bd. 2 (5), S. 331-341.
    DOI RIS ENW BIB
  • Grohs, Philipp; Liehr, Lukas (2022) On Foundational Discretization Barriers in STFT Phase Retrieval. J. Fourier Anal. Appl., Bd. 28 (2), S. ARTN 39.
    DOI RIS ENW BIB
  • Verdun, Claudio M.; Fuchs, Tim; Harar, Pavol; Elbrachter, Dennis; Fischer, David S. et al. [..] (2021) Group Testing for SARS-CoV-2 Allows for Up to 10-Fold Efficiency Increase Across Realistic Scenarios and Testing Strategies. FRONTIERS IN PUBLIC HEALTH, Bd. 9, S. ARTN 583377.
    DOI RIS ENW BIB
  • Elbraechter, Dennis; Grohs, Philipp; Jentzen, Arnulf; Schwab, Christoph (2021) DNN Expression Rate Analysis of High-Dimensional PDEs: Application to Option Pricing. Constr. Approx.
    DOI RIS ENW BIB
  • L Herrmann, C Schwab, J Zech (2020) Deep Neural Network Expression of Posterior Expectations in Bayesian PDE Inversion. Inverse Problems, Bd. 36 (12), S. 125011.
    DOIDownload RIS ENW BIB
  • Dick, J.; Ebert, A.; Herrmann, L.; Kritzer, P.; Longo, M. (online: 2023) The fast reduced QMC matrix-vector product. Journal of Computational and Applied Mathematics, Bd. 440, S. 115642.
    RIS ENW BIB
  • Abdeljawad, Ahmed; Grohs, Philipp (2022) Integral representations of shallow neural network with rectified power unit activation function. Neural Netw., Bd. 155, S. 536-550.
    DOI RIS ENW BIB
  • Grohs, Philipp; Rathmair, Martin (2022) Stable Gabor phase retrieval for multivariate functions. J. Eur. Math. Soc., Bd. 24 (5), S. 1593-1615.
    DOI RIS ENW BIB
  • Abdeljawad, Ahmed; Grohs, Philipp (2022) Approximations with deep neural networks in Sobolev time-space. Anal. Appl., Bd. 20 (03), S. 499-541.
    DOI RIS ENW BIB
  • Scherbela, Michael; Reisenhofer, Rafael; Gerard, Leon; Marquetand, Philipp; Grohs, Philipp (2022) Solving the electronic Schrodinger equation for multiple nuclear geometries with weight-sharing deep neural networks. NATURE COMPUTATIONAL SCIENCE, Bd. 2 (5), S. 331-341.
    DOI RIS ENW BIB
  • Grohs, Philipp; Liehr, Lukas (2022) On Foundational Discretization Barriers in STFT Phase Retrieval. J. Fourier Anal. Appl., Bd. 28 (2), S. ARTN 39.
    DOI RIS ENW BIB
  • Verdun, Claudio M.; Fuchs, Tim; Harar, Pavol; Elbrachter, Dennis; Fischer, David S. et al. [..] (2021) Group Testing for SARS-CoV-2 Allows for Up to 10-Fold Efficiency Increase Across Realistic Scenarios and Testing Strategies. FRONTIERS IN PUBLIC HEALTH, Bd. 9, S. ARTN 583377.
    DOI RIS ENW BIB
  • Elbraechter, Dennis; Grohs, Philipp; Jentzen, Arnulf; Schwab, Christoph (2021) DNN Expression Rate Analysis of High-Dimensional PDEs: Application to Option Pricing. Constr. Approx.
    DOI RIS ENW BIB
  • L Herrmann, C Schwab, J Zech (2020) Deep Neural Network Expression of Posterior Expectations in Bayesian PDE Inversion. Inverse Problems, Bd. 36 (12), S. 125011.
    DOIDownload RIS ENW BIB

Conference Contribution: Publication in Proceedings

  • L. Herrmann, C. Schwab (2020) Multilevel Quasi-Monte Carlo Uncertainty Quantification for Advection-Diffusion-Reaction. In: L'Ecuyer, P.; Tuffin, B. (Hrsg.), Monte Carlo and Quasi-Monte Carlo Methods 2018; Cham: Springer, S. 31-67.
    DOIDownload RIS ENW BIB
  • L. Herrmann, C. Schwab (2020) Multilevel Quasi-Monte Carlo Uncertainty Quantification for Advection-Diffusion-Reaction. In: L'Ecuyer, P.; Tuffin, B. (Hrsg.), Monte Carlo and Quasi-Monte Carlo Methods 2018; Cham: Springer, S. 31-67.
    DOIDownload RIS ENW BIB