Leopold Mareis
Leopold Mareis is a doctoral student in the field of applied mathematical statistics at the Technical University of Munich. He previously worked at the Fraunhofer Institute for Cognitive Systems IKS in the 'Reasoned AI Decisions' group. His research interest lies in the efficient estimation and uncertainty quantification of structural parameters in graphical modeling.
Session
Graphical models encode dependencies between variables through graphs whose implied statistical models obey algebraic constraints. We show how symbolic computation in the Julia package OSCAR enables causal effect estimation in such models. Using Groebner basis elimination, we resolve linear parameter identification beyond classical criteria and demonstrate a reproducible Julia workflow on a real data example.