The task of estimating causal effects from non-experimental data is notoriously difficult and unreliable. Nevertheless, precisely such estimates are commonly required in many fiel...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen...
Selection bias, caused by preferential exclusion of samples from the data, is a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized exper...
Current state-of-the-art planners solve problems, easy and hard alike, by search, expanding hundreds or thousands of nodes. Yet, given the ability of people to solve easy problems...
This paper describes an evolutionary method for identifying a causal model from the observed time series data. We use a system of ordinary differential equations (ODEs) as the cau...
The paper provides a uniform representation of abductive reasoning in the logical framework of causal inference relations. The representation covers in a single framework not only...