@InProceedings{garzon_et_al:LIPIcs.SAT.2022.3,
  author =	{Garz\'{o}n, Iv\'{a}n and Mesejo, Pablo and Gir\'{a}ldez-Cru, Jes\'{u}s},
  title =	{{On the Performance of Deep Generative Models of Realistic SAT Instances}},
  booktitle =	{25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)},
  pages =	{3:1--3:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-242-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{236},
  editor =	{Meel, Kuldeep S. and Strichman, Ofer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2022.3},
  URN =		{urn:nbn:de:0030-drops-166775},
  doi =		{10.4230/LIPIcs.SAT.2022.3},
  annote =	{Keywords: Realistic SAT generators, pseudo-industrial random SAT, deep generative models, deep learning}
}