Table of Contents

• Some Variations on the PC AlgorithmJoaquín Abellán, Manuel Gómez-Olmedo, Serafín Moral. 1-8 [doi]
• Learning Complex Bayesian Network Features for ClassificationPeter Antal, András Gezsi, Gabor Hullam, András Millinghoffer. 9-16 [doi]
• Literature Mining using Bayesian NetworksPeter Antal, András Millinghoffer. 17-24 [doi]
• Locally specified credal networksAlessandro Antonucci, Marco Zaffalon. 25-34 [doi]
• A Bayesian Network Framework for the Construction of Virtual Agents with Human-like BehaviourOlav Bangsø, N. Sondberg-Madsen, Finn Verner Jensen. 35-42 [doi]
• Loopy Propagation: the Convergence Error in Markov NetworksJanneke H. Bolt. 43-50 [doi]
• Preprocessing the MAP ProblemJanneke H. Bolt, Linda C. van der Gaag. 51-58 [doi]
• Quartet-Based Learning of Shallow Latent VariablesTao Chen, Nevin Lianwen Zhang. 59-66 [doi]
• Continuous Decision MTE Influence DiagramsBarry R. Cobb. 67-74 [doi]
• Discriminative Scoring of Bayesian Network Classifiers: a Comparative StudyA. J. Feelders, Jevgenijs Ivanovs. 75-82 [doi]
• The Independency tree model: a new approach for clustering and factorisationM. Julia Flores, José A. Gámez, Serafín Moral. 83-90 [doi]
• Learning the Tree Augmented Naive Bayes Classifier from incomplete datasetsOlivier François, Philippe Leray. 91-98 [doi]
• Lattices for Studying Monotonicity of Bayesian NetworksLinda C. van der Gaag, Silja Renooij, Petra L. Geenen. 99-106 [doi]
• Multi-dimensional Bayesian Network ClassifiersLinda C. van der Gaag, Peter R. de Waal. 107-114 [doi]
• Dependency networks based classifiers: learning models by using independenceJosé A. Gámez, Juan L. Mateo, Jose Miguel Puerta. 115-122 [doi]
• Unsupervised naive Bayes for data clustering with mixtures of truncated exponentialsJosé A. Gámez, Rafael Rumí, Antonio Salmerón. 123-130 [doi]
• Selecting Strategies for Infinite-Horizon Dynamic LIMIDSMarcel van Gerven, Francisco Javier Díez. 131-138 [doi]
• Sensitivity analysis of extreme inaccuracies in Gaussian Bayesian NetworksM. A. Gomez-Villegas, Paloma Main, R. Susi. 139-146 [doi]
• Learning Bayesian Networks Structure using Markov NetworksChristophe Gonzales, N. Jouve. 147-154 [doi]
• Estimation of linear, non-gaussian causal models in the presence of confounding latent variablesPatrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen. 155-162 [doi]
• Symmetric Causal Independence Models for ClassificationRasa Jurgelenaite, Tom Heskes. 163-170 [doi]
• Complexity Results for Enhanced Qualitative Probabilistic NetworksJohan Kwisthout, Gerard Tel. 171-178 [doi]
• Decision analysis with influence diagrams using Elvira s explanation facilitiesM. Luque, Francisco Javier Díez. 179-186 [doi]
• Dynamic importance sampling in Bayesian networks using factorisation of probability treesIrene Martínez, Carmelo Rodríguez, Antonio Salmerón. 187-194 [doi]
• Learning Semi-Markovian Causal Models using ExperimentsStijn Meganck, Sam Maes, Philippe Leray, Bernard Manderick. 195-206 [doi]
• Geometry of rank testsJason Morton, Lior Pachter, Anne Shiu, Bernd Sturmfels, Oliver Wienand. 207-214 [doi]
• An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical ModelsJens D. Nielsen, Manfred Jaeger. 215-222 [doi]
• Adapting Bayes Network Structures to Non-stationary DomainsSøren Holbech Nielsen, Thomas D. Nielsen. 223-230 [doi]
• Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoningKristian G. Olesen, Ole K. Hejlesen, R. Dessau, I. Beltoft, M. Trangeled. 231-238 [doi]
• Predictive Maintenance using Dynamic Probabilistic NetworksD. Ozgur-Unluakin, Taner Bilgiç. 239-246 [doi]
• Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak TransitivityJosé M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér. 247-254 [doi]
• Evidence and Scenario Sensitivities in Naive Bayesian ClassifiersSilja Renooij, Linda C. van der Gaag. 255-262 [doi]
• Abstraction and Refinement for Solving Continuous Markov Decision ProcessesAlberto Reyes, Pablo H. Ibargüengoytia, Luis Enrique Sucar, Eduardo F. Morales. 263-270 [doi]
• Bayesian Model Averaging of TAN Models for ClusteringGuzmán Santafé, José Antonio Lozano, Pedro Larrañaga. 271-278 [doi]
• Dynamic Weighting A* Search-based MAP Algorithm for Bayesian NetworksXiaoxun Sun, Marek J. Druzdzel, Changhe Yuan. 279-286 [doi]
• A Short Note on Discrete Representability of Independence ModelsPetr Simecek. 287-292 [doi]
• Evaluating Causal effects using Chain Event GraphsPeter Thwaites, Jim Smith. 293-300 [doi]
• Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class ModelsYi Wang, Nevin Lianwen Zhang. 301-308 [doi]
• Optimal Design with Design NetworksY. Xiang. 309-316 [doi]
• Hybrid Loopy Belief PropagationChanghe Yuan, Marek J. Druzdzel. 317-324 [doi]
• Probabilistic Independence of Causal InfluencesAdam Zagorecki, Marek J. Druzdzel. 325-332 [doi]