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Learning Complex Bayesian Network Features for Classification

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Literature Mining using Bayesian Networks

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Locally specified credal networks

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A Bayesian Network Framework for the Construction of Virtual Agents with Human-like Behaviour

J. H. Bolt
Loopy Propagation: the Convergence Error in Markov Networks

J. H. Bolt and L. C. van der Gaag
Preprocessing the MAP Problem

T. Chen and N. L. Zhang
Quartet-Based Learning of Shallow Latent Variables

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Continuous Decision MTE Influence Diagrams

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Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study

M. Julia Flores, J. A. Gamez, and S. Moral
The Independency tree model: a new approach for clustering and factorisation

O. C. H. Francois and P. Leray
Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets

L. C. van der Gaag, S. Renooij, and P. L. Geenen
Lattices for Studying Monotonicity of Bayesian Networks

L. C. van der Gaag and P. R. de Waal
Multi-dimensional Bayesian Network Classifiers

J. A. Gamez, J. L. Mateo, and J. M. Puerta
Dependency networks based classifiers: learning models by using independence

J. A. Gamez, R. Rumi, and A. Salmeron
Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials

M. A. J. van Gerven and F. J. Diez
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS

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Sensitivity analysis of extreme inaccuracies in Gaussian Bayesian Networks

C. Gonzales and N. Jouve
Learning Bayesian Networks Structure using Markov Networks

P. O. Hoyer, S. Shimizu, and A. J. Kerminen
Estimation of linear, non-gaussian causal models in the presence of confounding
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R. Jurgelenaite and T. Heskes
Symmetric Causal Independence Models for Classification

J. Kwisthout and G. Tel
Complexity Results for Enhanced Qualitative Probabilistic Networks

M. Luque and F. J. Diez
Decision analysis with influence diagrams using Elvira's explanation facilities

I. Martinez, C. Rodriguez, and A. Salmeron
Dynamic importance sampling in Bayesian networks using factorisation of probability trees

S. Meganck, S. Maes, P. Leray, and B. Manderick
Learning Semi-Markovian Causal Models using Experiments

J. Morton, L. Pachter, A. Shiu, B. Sturmfels, and O. Wienand
Geometry of rank tests

J. D. Nielsen and M. Jaeger
An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models

S. H. Nielsen and T. D. Nielsen
Adapting Bayes Network Structures to Non-stationary Domains

K. G. Olesen, O. K. Hejlesen, R. Dessau, I. Beltoft, and M. Trangeled
Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoning

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Predictive Maintenance using Dynamic Probabilistic Networks

J. M. Pena, R. Nilsson, J. Bjorkegren, and J. Tegner
Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity

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Evidence and Scenario Sensitivities in Naive Bayesian Classifiers

A. Reyes, P. Ibarguengoytia, L. E. Sucar, and E. Morales
Abstraction and Refinement for Solving Continuous Markov Decision Processes

G. Santafe, J. A. Lozano, and P. Larranaga
Bayesian Model Averaging of TAN Models for Clustering

X. Sun, M. J. Druzdzel, and C. Yuan
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks

P. Simecek
A Short Note on Discrete Representability of Independence Models

P. Thwaites and J. Smith
Evaluating Causal effects using Chain Event Graphs

Y. Wang and N. L. Zhang
Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models

Y. Xiang
Optimal Design with Design Networks

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Hybrid Loopy Belief Propagation

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Probabilistic Independence of Causal Influences