Predicting Propositional Satisfiability via End-to-End Learning

Chris Cameron, Rex Chen, Jason S. Hartford, Kevin Leyton-Brown. Predicting Propositional Satisfiability via End-to-End Learning. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020. pages 3324-3331, AAAI Press, 2020. [doi]

@inproceedings{CameronCHL20,
  title = {Predicting Propositional Satisfiability via End-to-End Learning},
  author = {Chris Cameron and Rex Chen and Jason S. Hartford and Kevin Leyton-Brown},
  year = {2020},
  url = {https://aaai.org/ojs/index.php/AAAI/article/view/5733},
  researchr = {https://researchr.org/publication/CameronCHL20},
  cites = {0},
  citedby = {0},
  pages = {3324-3331},
  booktitle = {The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020},
  publisher = {AAAI Press},
  isbn = {978-1-57735-823-7},
}