This short course covers recent developments in graphical and causal modeling in Statistics/Machine Learning. It is comprised of the following three lectures, each two hours long.
The course targets an audience with exposure to basic concepts in graphical and causal modeling (e.g., conditional independence, DAGs, d-separation, Markov equivalence, definition of causal effects/the do-operator).
June 25, June 27, and July 2, 2024
Location
Parkring 11, 2nd floor, Garching n. Munich
Seminar room: 8101.02.110
Online
https://tum-conf.zoom-x.de/j/65826319465?pwd=LlopeTZ8YaHF18ezkNS5nqC7jTb3WY.1
Meeting-ID: 658 2631 9465
Kenncode: 232588