Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Institut für Mathematik

Gregor Pasemann

Research assistant

Mathematical Statistics

 

Mail

gregor.pasemann (at) hu-berlin.de

 

Postal address

Humboldt-Universität zu Berlin

Institut für Mathematik

Unter den Linden 6

D-10099 Berlin

 

Office

Room 1.209

Rudower Chaussee 25

12489 Berlin (Adlershof)

 

Teaching

 

  • WS 22/23: Statistik Stochastischer Prozesse (Statistics of Stochastic Processes). Ankündigung (DE/EN)

 

 

Publications / Preprints

 

  1. G. Pasemann, M. Reiß (2025+). Nonparametric Diffusivity Estimation for the Stochastic Heat Equation from Noisy Observations. arXiv:2410.00677
  2. G. Pasemann, C. Beta, W. Stannat (2025+). Stochastic Reaction-Diffusion Systems in Biophysics: Towards a Toolbox for Quantitative Model Evaluation. arXiv:2307.06655
  3. I. Cialenco, H.-J. Kim, G. Pasemann (2023). Statistical analysis of discretely sampled semilinear SPDEs: a power variation approach. Stoch PDE: Anal Comp 12, 326–351. doi:10.1007/s40072-022-00285-3
  4. R. Altmeyer, I. Cialenco, G. Pasemann (2023). Parameter estimation for semilinear SPDEs from local measurements. Bernoulli 29(3), 2035–2061. doi:10.3150/22-BEJ1531
  5. G. Pasemann, S. Flemming, S. Alonso, C. Beta, W. Stannat (2021). Diffusivity Estimation for Activator-Inhibitor Models: Theory and Application to Intracellular Dynamics of the Actin Cytoskeleton. J Nonlinear Sci 31, 59. doi:10.1007/s00332-021-09714-4
  6. G. Pasemann, W. Stannat (2020). Drift estimation for stochastic reaction-diffusion systems. Electron. J. Statist. 14(1) 547-579. doi:10.1214/19-EJS1665

 

Thesis

  • G. Pasemann (2021). Parameter estimation for semilinear stochastic partial differential equations. Dissertation, TU Berlin. doi:10.14279/depositonce-12552