37 citations · 59 across the 3 of their papers we have counts for
3 papers
cs.AI2013★ 37 cited
A Sound and Complete Algorithm for Learning Causal Models from Relational Data
Marc Maier, Katerina Marazopoulou, David Arbour +1
The PC algorithm learns maximally oriented causal Bayesian networks. However, there is no equivalent complete algorithm for learning the structure of relational models, a more expr…
cs.AI2013★ 22 cited
Reasoning about Independence in Probabilistic Models of Relational Data
Marc Maier, Katerina Marazopoulou, David Jensen
We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to t…
cs.AI2012
Identifying Independence in Relational Models
Marc Maier, David Jensen
The rules of d-separation provide a framework for deriving conditional independence facts from model structure. However, this theory only applies to simple directed graphical model…