Current Group Member

M.Sc. Leonie Kreis

PhD Student

Current and Upcoming Projects

Multilevel Architectures and Algorithms in Deep Learning
Start: 2023-01-01
End: 2025-12-31
Principal Investigators: Roland Herzog, Anton Schiela
Staff: Leonie Kreis, Frederik Köhne
Funded by: DFG within the Priority Program funding scheme
Part of: Theoretical Foundations of Deep Learning (SPP 2298)

Recent Completed Projects

Latest Publications

  • Roland Herzog, Frederik Köhne, Leonie Kreis and Anton Schiela
    Metric Frobenius norms and inner products of matrices and linear maps
    Linear Algebra and its Applications 727, p.112-128, 2025
    arXiv:2311.15419
    doi:10.1016/j.laa.2025.08.005
    bibtex 
    @ARTICLE{HerzogKoehneKreisSchiela:2025:1,
  AUTHOR = {Herzog, Roland and Köhne, Frederik and Kreis, Leonie and Schiela, Anton},
  DATE = {2025-08-08},
  DOI = {10.1016/j.laa.2025.08.005},
  EPRINT = {2311.15419},
  EPRINTTYPE = {arXiv},
  JOURNALTITLE = {Linear Algebra and its Applications},
  PAGES = {112--128},
  TITLE = {Metric Frobenius norms and inner products of matrices and linear maps},
  VOLUME = {727},
}
  • Evelyn Herberg, Roland Herzog, Frederik Köhne, Leonie Kreis and Anton Schiela
    Sensitivity-based layer insertion for residual and feedforward neural networks, 2023
    arXiv:2311.15995
    bibtex 
    @ONLINE{HerbergHerzogKoehneKreisSchiela:2023:1,
  AUTHOR = {Herberg, Evelyn and Herzog, Roland and Köhne, Frederik and Kreis, Leonie and Schiela, Anton},
  DATE = {2023-11},
  EPRINT = {2311.15995},
  EPRINTTYPE = {arXiv},
  TITLE = {Sensitivity-based layer insertion for residual and feedforward neural networks},
}
  • Frederik Köhne, Leonie Kreis, Anton Schiela and Roland Herzog
    Adaptive step sizes for preconditioned stochastic gradient descent, 2023
    arXiv:2311.16956
    bibtex 
    @ONLINE{KoehneKreisSchielaHerzog:2023:1,
  AUTHOR = {Köhne, Frederik and Kreis, Leonie and Schiela, Anton and Herzog, Roland},
  DATE = {2023-11},
  EPRINT = {2311.16956},
  EPRINTTYPE = {arXiv},
  TITLE = {Adaptive step sizes for preconditioned stochastic gradient descent},
}

Recent Teaching