25 citations · 29 across the 2 of their papers we have counts for
3 papers
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data
Krzysztof Chalupka, Tobias Bischoff, Pietro Perona +1
We show that the climate phenomena of El Nino and La Nina arise naturally as states of macro-variables when our recent causal feature learning framework (Chalupka 2015, Chalupka 20…
Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
Much of scientific data is collected as randomized experiments intervening on some and observing other variables of interest. Quite often, a given phenomenon is investigated in sev…
On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables
Frederick Eberhardt, Clark Glymour, Richard Scheines
We show that if any number of variables are allowed to be simultaneously and independently randomized in any one experiment, log2(N) + 1 experiments are sufficient and in the worst…