Team overview page 〉Details for: Hans Olischläger
Research interests:
Bayesian and Simulation-Based Inference, Generative Models, Strictly Proper Scoring Rules, Nonlinear Dynamics, Pattern Formation, Climate Modelling, Forecasting
Short summary of current research:
Bayesian methods are now one of the predominant statistical analysis frameworks. They provide a clear recipe for incorporating prior knowledge and understanding of a given process with observations in the real world. Simulation-Based Inference methods let us give even the most complex statistical models (like global climate forecasts) such a proper statistical treatment. I work on the intersection of generative modelling and statistics, aiming to build and share trustworthy (diagnosable) methods applicable to more and more scientific domains.