You are all cordially invited to the AMLab seminar on Tuesday March 21 at 16:00 in C3.163, where Frederick Eberhardt (Caltech) will give a talk titled “Causal Macro Variables”. Afterwards there are the usual drinks and snacks!
Abstract: Standard methods of causal discovery take as input a statistical data set of measurements of well-defined causal variables. The goal is then to determine the causal relations among these variables. But how are these causal variables identified or constructed in the first place? Often we have sensor level data but assume that the relevant causal interactions occur at a higher scale of aggregation. Sometimes we only have aggregate measurements of causal interactions at a finer scale. I will present recent work on a framework and method for the construction and identification of causal macro-variables that ensures that the resulting causal variables have well-defined intervention distributions. We have applied this approach to large scale climate data, for which we were able to identify the macro-phenomenon of El Nino using an unsupervised method on micro-level sea surface temperature and wind measurements over the equatorial Pacific.