Geodesy

Quantum mechanics

Benchmark (surveying)

Causal inference

Knowledge extraction

Economics

Computer science

Causal structure

Physics

Optics

Geography

Causal model

Econometrics

Focus (optics)

Data science

Artificial intelligence

Medicine

Causality (physics)

Pathology

ACM Computing Surveys

Causal reasoning is a crucial part of science and human intelligence. In order to discover causal relationships from data, we need structure discovery methods. We provide a review of background theory and a survey of methods for structure discovery. We primarily focus on modern, continuous optimization methods, and provide reference to further resources such as benchmark datasets and software packages. Finally, we discuss the assumptive leap required to take us from structure to causality.

D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery