Speaker: Thomas Richardson, University of Washington
Place: nav.tum.de/room/8101.02.110 (Garching Hochbrück)
- Lecture 1: “Learning from conditional independence when not all variables are measured: Ancestral graphs and the FCI algorithm”
Time: June 25, 14:00-16:00, Room 8101.02.110 in Parkring 13, Garching-Hochbrück (2. Stock)
- Lecture 2: “Identification of causal effects: A reformulation of the ID algorithm via the fixing operation”
Time: June 27, 14:00-16:00, Room 8101.02.110 in Parkring 13, Garching-Hochbrück (2. Stock)
- Lecture 3: “Nested Markov Models”
Time: 2. July, 14:00-16:00, Raum 8101.02.110 im Parkring 13, Garching-Hochbrück (2. Stock)
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).