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Accepted papers

Alessandro Antonucci, Giorgio Corani and Sandra Gabaglio Active Learning by the Naive Credal Classifier
Manuel Arias, Francisco Javier Díez, Miguel Ángel Palacios-Alonso and Íñigo Bermejo ProbModelXML. A format for encoding probabilistic graphical models
Victor Bellon, Jesús Cerquides and Ivo Grosse Gaussian Join Tree classifiers with applications to mass spectra classification
Íñigo Bermejo, Jesús Oliva, Francisco Javier Díez and Manuel Arias Interactive learning of Bayesian Networks with OpenMarkov
Giorgos Borboudakis and Ioannis Tsamardinos Tools and Algorithms for Causally Interpreting Directed Edges in Maximal Ancestral Graphs
Rafael Cabañas de Paz, Manuel Gómez-Olmedo and Andrés Cano Approximate Inference in Influence Diagrams using Binary Trees
Suming Chen, Arthur Choi and Adnan Darwiche The Same-Decision Probability: A New Tool for Decision Making
Barry Cobb and Prakash Shenoy Piecewise Linear Approximations of Nonlinear Deterministic Conditionals in Hybrid Bayesian Networks
Barry Cobb, Rafael Rumi and Antonio Salmeron Approximating the Distribution of a Sum of Log-normal Random Variables
Giorgio Corani, Cristina Magli, Alessandro Giusti, Luca Gianaroli and Luca Gambardella A Bayesian Network model for predicting the outcome of in vitro fertilization
Francisco Javier Díez, Manuel Luque and Caroline König Decision analysis networks
Ralf Eggeling, Pierre-Yves Bourguignon, André Gohr and Ivo Grosse Gibbs sampling for parsimonious Markov models with latent variables
Sander Evers and Peter Lucas A framework for development, teaching and deployment of inference algorithms
M. Julia Flores, Jose A. Gamez and Ana M. Martínez Meta-prediction of semi-naive Bayesian network classifiers based on dataset complexity characterization
Perry Groot and Peter Lucas Gaussian Process Regression with Censored Data Using Expectation Propagation
Alain Hauser and Peter Bühlmann Two Optimal Strategies for Active Learning of Causal Models from Interventions
Maarten van der Heijden and Peter Lucas Probabilistic reasoning with temporal indeterminacy
Pablo Hernandez-Leal, Felipe Orihuela-Espina, L. Enrique Sucar and Eduardo F. Morales Hybrid Binary-Chain Multi-label Classifiers
Gabor Hullam and Peter Antal Estimation of effect size posterior using model averaging over Bayesian network structures and parameters
Sergey Kirshner Latent Tree Copulas
Helge Langseth, Thomas D. Nielsen and Antonio Salmeron Learning Mixtures of Truncated Basis Functions from Data
Helge Langseth, Thomas D. Nielsen, Rafael Rumí Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions
Martijn Lappenschaar, Arjen Hommersom and Peter Lucas Qualitative Chain Graphs and their Use in Medicine
Chao Li and Maomi Ueno A Depth-First Search Algorithm for Optimal Triangulation of Bayesian Network
Václav Lín Decision-Theoretic Troubleshooting: Hardness of Approximation
Tengfei Liu, Nevin L. Zhang, Kin Man Poon, Hua Liu and Yi Wang A Novel LTM-based Method for Multidimensional Clustering
Pedro Luis López-Cruz, Concha Bielza and Pedro Larrañaga Learning mixtures of polynomials from data using B-spline interpolation
Anna Lupinska-Dubicka and Marek Druzdzel A Comparison of Popular Fertility Awareness Methods to a DBN Model of the Woman's Monthy Cycle
Anders Madsen and Cory Butz On the Importance of Elimination Heuristics in Lazy Propagation
Brandon Malone and Changhe Yuan A Bounded Error, Anytime, Parallel Algorithm for Exact Bayesian Network Structure Learning
Andrés R. Masegosa and Serafín Moral An interactive approach for cleaning noisy observations in Bayesian networks with the help of an expert
Jose M. Peña Learning AMP Chain Graphs under Faithfulness
Cora B. Pérez-Ariza, Ann E. Nicholson and M. Julia Flores Prediction of Coffee Rust Disease Using Bayesian Networks
Silja Renooij Generalised Co-variation for Sensitivity Analysis in Bayesian Networks
Rafael Rumi, Antonio Salmerón and Prakash P. Shenoy Tractable inference in hybrid Bayesian networks with deterministic conditionals using re-approximations
François Schnitzler, Pierre Geurts and Louis Wehenkel Mixtures of Bagged Markov Tree Ensembles
Nathaniel Shiers and Jim Q. Smith Graphical inequality diagnostics for phylogenetic trees
Dag Sonntag and Jose M. Peña Learning Multivariate Regression Chain Graphs under Faithfulness
Milan Studeny Integer linear programming approach to learning Bayesian network structure
Joe Suzuki The Bayesian Chow-Liu Algorithm
Inma Tur and Robert Castelo Learning high-dimensional mixed graphical models with missing values
Maomi Ueno and Masaki Uto Non-Informative Dirichlet Score for learning Bayesian networks
Jimmy Vandel, Simon De Givry and Brigitte Mangin New Local Move Operators for Bayesian Network Structure Learning
Kristin Vogel, Carsten Riggelsen, Bruno Merz, Heidi Kreibich and Frank Scherbaum Flood Damage and Influencing Factors: A Bayesian Network Perspective
Jirka Vomlel and Petr Tichavsky Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition
Yang Xiang Bayesian Network Inference With NIN-AND Tree Models

The workshop is hosted by the Department of Computer Science and Artificial Intelligence, Granada University, Spain.