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