Probabilistic Model Counting with Short XORs

Author:

Achlioptas Dimitris,Theodoropoulos Panos

Publisher

Springer International Publishing

Reference18 articles.

1. Chakraborty, S., Fremont, D.J., Meel, K.S., Seshia, S.A., Vardi, M.Y.: Distribution-aware sampling and weighted model counting for SAT. In: Brodley, C.E., Stone, P. (eds.) Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada, 27–31 July 2014, pp. 1722–1730. AAAI Press (2014)

2. Lecture Notes in Computer Science;S Chakraborty,2013

3. Lecture Notes in Computer Science;S Chakraborty,2013

4. Chakraborty, S., Meel, K.S., Vardi, M.Y.: Balancing scalability and uniformity in SAT witness generator. In: The 51st Annual Design Automation Conference 2014, DAC 2014, San Francisco, CA, USA, 1–5 June 2014, pp. 60:1–60:6. ACM (2014)

5. Chakraborty, S., Meel, K.S., Vardi, M.Y.: Algorithmic improvements in approximate counting for probabilistic inference: from linear to logarithmic SAT calls. In: Kambhampati, S. (ed.) Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9–15 July 2016, pp. 3569–3576. IJCAI/AAAI Press (2016)

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