Cyclic functional causal models over finite variables get a unique probability rule and a sound and complete graph-separation property (p-separation) that reduces to d-separation in acyclic graphs.
Quantifying causality in data sci- ence with quasi-experiments
1 Pith paper cite this work, alongside 34 external citations. Polarity classification is still indexing.
1
Pith paper citing it
34
external citations · OpenAlex
citation-role summary
background 1
citation-polarity summary
fields
math.ST 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Cyclic functional causal models beyond unique solvability with a graph separation theorem
Cyclic functional causal models over finite variables get a unique probability rule and a sound and complete graph-separation property (p-separation) that reduces to d-separation in acyclic graphs.