Probabilistic independence networks for hidden Markov probability models
Neural Computation
From Logic to Logic Programming
From Logic to Logic Programming
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Efficient fixpoint computation in linear tabling
Proceedings of the 5th ACM SIGPLAN international conference on Principles and practice of declaritive programming
Case-factor diagrams for structured probabilistic modeling
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
Compiling Bayesian networks with local structure
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Generalized queries on probabilistic context-free grammars
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
A glimpse of symbolic-statistical modeling by PRISM
Journal of Intelligent Information Systems
Variational Bayes via propositionalized probability computation in PRISM
Annals of Mathematics and Artificial Intelligence
Logic-Based Probabilistic Modeling
WoLLIC '09 Proceedings of the 16th International Workshop on Logic, Language, Information and Computation
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
| Hi-index | 0.00 |
In this paper we prove that the well-known correspondence between the forward-backward algorithm for hidden Markov models (HMMs) and belief propagation (BP) applied to HMMs can be generalized to one between BP for junction trees and the generalized inside-outside probability computation for probabilistic logic programs applied to junction trees.