Equivalence and synthesis of causal models
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Learning equivalence classes of bayesian-network structures
The Journal of Machine Learning Research
Optimal structure identification with greedy search
The Journal of Machine Learning Research
Minds and Machines
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Finding a DAG to represent a Markov equivalence class of DAGs -- i.e., a pattern -- is a necessary step in some causal discovery algorithms. If the case involves a known true DAG generating artificial data, then it is also arguably a necessary step in evaluating any causal discovery algorithm. We present three algorithms for converting patterns to representative DAGs, analyse their time complexity and demonstrate their use experimentally.