Applied Probability Theory

Investigation of basic questions of probability theory:

Consistent designation of prior-probabilities using differential geometry

Outlier tolerant parameter estimates

Correlated random tests

Simulation of hierarchic models

Numerical methods for high-dimensional, multi-modal probability densities

Badly conditioned inversion problems

Results are applied in the following fields:

Analysis of results generated by Quantum Monte Carlo
Complex data analysis in experimental physics
- Ellipsometry
- Tomography, Abel inversion
- Mass-spectroscopy
- Deconvolution and reconstruction of spectral functions