Staff Dr. Tim Jahn

Address:
Institut für Numerische Simulation
Friedrich-Hirzebruch-Allee 7
53115 Bonn
Phone: +49 228 73-69813
Office: FHA7 3.005
E-Mail: ed tod nnob-inu tod sni ta nhaja tod b@foo tod de

Teaching

Winter semester 2021/22

See teaching activities of the whole group.

Publications

2023

  1. Regularizing linear inverse problems under unknown non-gaussian white noise allowing repeated measurements. B. Harrach, T. Jahn, and R. Potthast. IMA Journal of Numerical Analysis, 43(1):443–500, 2023. BibTeX arxiv
  2. Noise level free regularisation of general linear inverse problems under unconstrained white noise. T. Jahn. SIAM/ASA J. Uncertain. Quantif., 2023. accepted for publication. BibTeX arxiv

2022

  1. A probabilistic oracle inequality and quantification of uncertainty of a modified discrepancy principle for statistical inverse problems. T. Jahn. Electronic Transactions on Numerical Analysis, 57:35–56, 2022. BibTeX DOI arxiv
  2. Discretisation-adaptive regularisation of statistical inverse problems. T. Jahn. Universität Bonn, 2022. BibTeX arxiv
  3. Optimal convergence of the discrepancy principle for polynomially and exponentially ill-posed operators under white noise. T. Jahn. Numerical Functional Analysis and Optimization, 43(2):145–167, 2022. BibTeX DOI arXiv arxiv

2021

  1. A modified discrepancy principle to attain optimal convergence rates under unknown noise. T. Jahn. Inverse Problems, 37(9):095008, 2021. BibTeX DOI arxiv

2020

  1. Beyond the bakushinkii veto: regularising linear inverse problems without knowing the noise distribution. B. Harrach, T. Jahn, and R. Potthast. Numerische Mathematik, 145(3):581–603, 2020. BibTeX DOI arxiv
  2. On the discrepancy principle for stochastic gradient descent. T. Jahn and B. Jin. Inverse Problems, 36(9):095009, 2020. BibTeX DOI arxiv
  3. Regularising linear inverse problems under unknown non-Gaussian noise. T. N. Jahn. PhD thesis, Institute for Mathematics, Johann Wolfgang Goethe-Universität Frankfurt am Main, 2020. BibTeX PDF

2016

  1. The high temperature regime of a multi-species mean field spin glass. T. Jahn. Master's thesis, Insititute for Mathematics, Johann Wolfgang Goethe-Universität Frankfurt am Main, 2016. BibTeX PDF

2015

  1. Limit cycles of neuron controlled robots in simulated physical environment. T. Jahn. Bachelor's Thesis, Institute for Theoretical Physics, Johann Wolfgang Goethe-Universität Frankfurt am Main, 2015. BibTeX PDF
  2. The sensorimotor loop as a dynamical system: how regular motion primitives may emerge from self-organized limit cycles. B. Sándor, T. Jahn, L. Martin, and C. Gros. Frontiers in Robotics and AI, 2:31, 2015. BibTeX DOI