Operations Research
International Journal of Approximate Reasoning
A model for reasoning about persistence and causation
Computational Intelligence
A computational scheme for reasoning in dynamic probabilistic networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Objective probabilities in expert systems
Artificial Intelligence
Finding MAPs for belief networks is NP-hard
Artificial Intelligence
Decision-theoretic troubleshooting
Communications of the ACM
The normative representation of quantified beliefs by belief functions
Artificial Intelligence
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Machine Learning - Special issue on learning with probabilistic representations
Efficient Approximations for the MarginalLikelihood of Bayesian Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Graphical models for machine learning and digital communication
Graphical models for machine learning and digital communication
Estimating dependency structure as a hidden variable
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
A Comparison of Graphical Techniques for Asymmetric Decision Problems
Management Science
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering
Pattern Recognition Letters
Importance sampling in Bayesian networks using probability trees
Computational Statistics & Data Analysis
Artificial Intelligence
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
The Art of Causal Conjecture
Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction
Machine Learning - Special issue: Unsupervised learning
Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems
Statistics and Computing
On predictive distributions and Bayesian networks
Statistics and Computing
Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Factorized Distribution Algorithm Using Single Connected Bayesian Networks
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Incremental Learning of Tree Augmented Naive Bayes Classifiers
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Influence Diagrams for Neonatal Jaundice Management
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
an entropy-driven system for construction of probabilistic expert systems from databases
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Learning Bayesian Belief Network Classifiers: Algorithms and System
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Technologies for constructing intelligent systems
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Floating search algorithm for structure learning of Bayesian network classifiers
Pattern Recognition Letters
Machine Learning
Probabilistic graphical models and algorithms for genomic analysis
Probabilistic graphical models and algorithms for genomic analysis
Estimation of Distribution Algorithms with Kikuchi Approximations
Evolutionary Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing)
Complexity results and approximation strategies for MAP explanations
Journal of Artificial Intelligence Research
MUNIN: a causal probabilistic network for interpretation of electromyographic findings
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Explanation, irrelevance and statistical independence
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
The paradoxical success of fuzzy logic
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Unconstrained influence diagrams
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Being Bayesian about network structure
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Representing and solving asymmetric Bayesian decision problems
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Evaluating influence diagrams using LIMIDs
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
An anytime algorithm for decision making under uncertainty
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Learning mixtures of DAG models
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Object-oriented Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Why is diagnosis using belief networks insensitive to imprecision in probabilities?
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Geometric implications of the naive Bayes assumption
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Induction of selective Bayesian classifiers
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
IEEE Transactions on Evolutionary Computation
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Approximating discrete probability distributions with dependence trees
IEEE Transactions on Information Theory
Scenario analysis using Bayesian networks: A case study in energy sector
Knowledge-Based Systems
Answering queries in hybrid Bayesian networks using importance sampling
Decision Support Systems
A review on probabilistic graphical models in evolutionary computation
Journal of Heuristics
A Bayesian network for burr detection in the drilling process
Journal of Intelligent Manufacturing
A review on evolutionary algorithms in Bayesian network learning and inference tasks
Information Sciences: an International Journal
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In this paper, we review the role of probabilistic graphical models in artificial intelligence. We start by giving an account of the early years when there was important controversy about the suitability of probability for intelligent systems. We then discuss the main milestones for the foundations of graphical models starting with Pearl's pioneering work. Some of the main techniques for problem solving (abduction, classification, and decision-making) are briefly explained. Finally, we propose some important challenges for future research and highlight relevant applications (forensic reasoning, genomics and the use of graphical models as a general optimization tool).