Thomas Müller

Doctoral Researcher
TU Berlin

Research profile

Thomas Müller works on mathematical statistics for stochastic differential equations (SDEs), with a particular focus on how numerical approximation affects statistical inference. His first project investigates the impact of discretization schemes on parameter estimation for SDE models. He also brings prior experience in likelihood-based inference from his master’s thesis, in which he worked on maximum likelihood estimation for hidden Markov models.

Research areas

Machine Learning · Mathematical Statistics · Numerics

Five research keywords

Scientific machine learning · Parameter inference for stochastic processes · Likelihood-based inference · Statistical algorithms · Numerical discretization schemes