Presentation.
This seminar explores advanced aspects of causal inference and is ideally taken in after an introductory or advanced lecture on causal inference. Topics can be flexibly chosen and include theoretical, methodological, and practical challenges in causal discovery and effect estimation, such as developing a new method or theoretical result addressing a specific challenge in causal inference, conducting a numerical benchmark, or implementing and testing a new feature in the Tigramite Python causal inference package.
