Ordering-Based Causal Discovery for Linear and Nonlinear Relations
Ordering-Based Causal Discovery for Linear and Nonlinear Relations
Identifying causal relations from purely observational data typically requires additional assumptions on relations and/or noise. Most current methods restrict their analysis to datasets that are assumed to have pure linear or nonlinear relations, which is often not reflective of real-world datasets that contain a combination of both. This paper presents …