The observational characteristics of a linear structural equation model can
be effectively described by polynomial constraints on the observed covariance
matrix. However, these polynomials can be exponentially large, making them
impractical for many purposes. In this paper, we present a graphical notation
for many of these polynomial constraints. The expressive power of this notation
is investigated both theoretically and empirically.Comment: To appear in the proceedings of the 11th International Conference on
Probabilistic Graphical Models (PGM 2022
