Counting Background Knowledge Consistent Markov Equivalent Directed Acyclic Graphs

@InProceedings{pmlr-v216-sharma23b,
  title = 	 {Counting Background Knowledge Consistent {M}arkov Equivalent Directed Acyclic Graphs},
  author =       {Sharma, Vidya Sagar},
  booktitle = 	 {Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence},
  pages = 	 {1911--1920},
  year = 	 {2023},
  editor = 	 {Evans, Robin J. and Shpitser, Ilya},
  volume = 	 {216},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {31 Jul--04 Aug},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v216/sharma23b/sharma23b.pdf},
  url = 	 {https://proceedings.mlr.press/v216/sharma23b.html},
  abstract = 	 {We study the problem of counting the number of directed acyclic graphs in a Markov equivalence class (MEC) that are consistent with