On the complexity of inference about probabilistic relational models
- 31 March 2000
- journal article
- Published by Elsevier in Artificial Intelligence
- Vol. 117 (2) , 297-308
- https://doi.org/10.1016/s0004-3702(99)00109-5
Abstract
No abstract availableKeywords
This publication has 16 references indexed in Scilit:
- Convergence results for relational Bayesian networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Learning Probabilistic Relational ModelsPublished by Springer Nature ,2001
- Anytime deduction for probabilistic logicArtificial Intelligence, 1994
- Generating Bayesian Networks from Probability Logic Knowledge BasesPublished by Elsevier ,1994
- Approximating probabilistic inference in Bayesian belief networks is NP-hardArtificial Intelligence, 1993
- CONSTRUCTION OF BELIEF AND DECISION NETWORKSComputational Intelligence, 1992
- The computational complexity of probabilistic inference using bayesian belief networksArtificial Intelligence, 1990
- A Catalog of Complexity ClassesPublished by Elsevier ,1990
- Propagating Uncertainty in Bayesian Networks by Probabilistic Logic SamplingPublished by Elsevier ,1988
- Turing machines and the spectra of first-order formulas with equalityPublished by Association for Computing Machinery (ACM) ,1972