Title

Authors

  • Robert Ganian Vienna University of Technology
  • Thekla Hamm Vienna University of Technology
  • Topi Talvitie University of Helsinki

DOI:

https://doi.org/10.1609/aaai.v34i06.6573

Abstract

We consider the problem of counting the number of DAGs which are Markov-equivalent, i.e., which encode the same conditional independencies between random variables. The problem has been studied, among others, in the context of causal discovery, and it is known that it reduces to counting the number of so-called moral acyclic orientations of certain undirected graphs, notably chordal graphs.

Our main empirical contribution is a new algorithm which outperforms previously known exact algorithms for the considered problem by a significant margin. On the theoretical side, we show that our algorithm is guaranteed to run in polynomial time on a broad class of chordal graphs, including interval graphs.

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Published

2020-04-03

How to Cite

Ganian, R., Hamm, T., & Talvitie, T. (2020). Title. Proceedings of the AAAI Conference on Artificial Intelligence, 34(06), 10136-10143. https://doi.org/10.1609/aaai.v34i06.6573

Issue

Section

AAAI Technical Track: Reasoning under Uncertainty