Structural Sensitivity for the Knowledge Engineering of Bayesian Networks -- A Pairwise Class Interaction Framework for Multilabel Classification -- From Information to Evidence in a Bayesian Network -- Learning Gated Bayesian Networks for Algorithmic Trading -- Local Sensitivity of Bayesian Networks to Multiple Simultaneous Parameter Shifts -- Bayesian Network Inference Using Marginal Trees -- On SPI-Lazy Evaluation of Influence Diagrams -- Extended Probability Trees for Probabilistic Graphical Models -- Mixture of Polynomials Probability Distributions for Grouped Sample Data -- Trading off Speed and Accuracy in Multilabel Classification -- Robustifying the Viterbi algorithm -- Extended Tree Augmented Naive Classifier -- Evaluation of Rules for Coping with Insufficient Data in Constraint-based Search Algorithms -- Supervised Classification Using Hybrid Probabilistic Decision Graphs -- Towards a Bayesian Decision Theoretic Analysis of Contextual Effect Modifiers -- Discrete Bayesian Network Interpretation of the Cox's Proportional Hazards Model -- Minimizing Relative Entropy in Hierarchical Predictive Coding -- Treewidth and the Computational Complexity of MAP Approximations -- Bayesian Networks with Function Nodes -- A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs -- Equivalences Between Maximum A Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams -- Speeding Up $k$-Neighborhood Local Search in Limited Memory Influence Diagrams -- Inhibited Effects in CP-logic -- Learning Parameters in Canonical Models using Weighted Least Squares -- Learning Marginal AMP Chain Graphs under Faithfulness -- Learning Maximum Weighted (k+1)-order Decomposable Graphs by Integer Linear Programming -- Multi-label Classification for Tree and Directed Acyclic Graphs Hierarchies -- Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks -- Causal Discovery from Databases with Discrete and Continuous Variables -- On Expressiveness of the AMP Chain Graph Interpretation -- Learning Bayesian Network Structures  when Discrete and Continuous Variables are Present -- Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery -- Causal Independence Models for Continuous Time Bayesian Networks -- Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-Label Classification -- An Approximate Tensor-Based Inference Method Applied to the Game of Minesweeper -- Compression of Bayesian Networks with NIN-AND Tree Modeling -- A Study of Recently Discovered Equalities about Latent Tree Models using Inverse Edges -- An Extended MPL-C Model for Bayesian Network Parameter Learning with Exterior Constraints.