This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
1 describe an approach to the problem of forming hypotheses about hidden mechanisms w; thin devices — the "black box" problem for physical systems. The approach involv...
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...
The term “changes in structure,” originating from work in econometrics, refers to structural modifications invoked by actions on a causal model. In this paper we formalize the...
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...