PGM 2018

45 papers

A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks Ioan Gabriel Bucur, Tom Bussel, Tom Claassen, Tom Heskes

A Lattice Representation of Independence Relations Linda C. van der Gaag, Marco Baioletti, Janneke H. Bolt

A Novel Approach to Handle Inference in Discrete Markov Networks with Large Label Sets Alexander Oliver Mader, Jens Berg, Cristian Lorenz, Carsten Meyer

A Partial Orthogonalization Method for Simulating Covariance and Concentration Graph Matrices Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga

A Sum-Product Algorithm with Polynomials for Computing Exact Derivatives of the Likelihood in Bayesian Networks Alexandra Lefebvre, Grégory Nuel

An Empirical Study of Methods for SPN Learning and Inference Cory J. Butz, Jhonatan S. Oliveira, André E. Santos, André L. Teixeira, Pascal Poupart, Agastya Kalra

An Order-Based Algorithm for Learning Structure of Bayesian Networks Shahab Behjati, Hamid Beigy

Approximating the Maximum Weighted Decomposable Graph Problem with Applications to Probabilistic Graphical Models Aritz Pérez, Christian Blum, Jose A. Lozano

Bayesian Network Classifiers Under the Ensemble Perspective Jacinto Arias, José A. Gámez, José M. Puerta

Bayesian Network Structure Learning with Side Constraints Andrew Li, Peter Beek

Cascading Sum-Product Networks Using Robustness Diarmaid Conaty, Jesús Martínez Del Rincon, Cassio P. De Campos

Causal Structure Learning via Temporal Markov Networks Aubrey Barnard, David Page

Circular Chain Classifiers Jesús Joel Rivas, Felipe Orihuela-Espina, Luis Enrique Succar

Consistent Estimation Given Missing Data Karthika Mohan, Judea Pearl

Differential Networking with Path Weights in Gaussian Trees Alberto Roverato, Robert Castelo

Discrete Model-Based Clustering with Overlapping Subsets of Attributes Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza

Discriminative Training of Sum-Product Networks by Extended Baum-Welch Abdullah Rashwan, Pascal Poupart, Chen Zhitang

Exact Learning Augmented Naive Bayes Classifier Shouta Sugahara, Masaki Uto, Maomi Ueno

Finding Minimal Separators in LWF Chain Graphs Mohammad Ali Javidian, Marco Valtorta

Finding Optimal Bayesian Networks with Local Structure Topi Talvitie, Ralf Eggeling, Mikko Koivisto

Formal Verification of Bayesian Network Classifiers Andy Shih, Arthur Choi, Adnan Darwiche

Forward-Backward Splitting for Time-Varying Graphical Models Federico Tomasi, Veronica Tozzo, Alessandro Verri, Saverio Salzo

Instance-Specific Bayesian Network Structure Learning Fattaneh Jabbari, Shyam Visweswaran, Gregory F. Cooper

Intervals of Causal Effects for Learning Causal Graphical Models Samuel Montero-Hernandez, Felipe Orihuela-Espina, Luis Enrique Sucar

Learning Bayesian Network Classifiers with Completed Partially Directed Acyclic Graphs Bojan Mihaljević, Concha Bielza, Pedro Larrañaga

Learning Bayesian Networks by Branching on Constraints Thijs van Ommen

Learning Non-Parametric Markov Networks with Mutual Information Janne Leppä-Aho, Santeri Räisänen, Xiao Yang, Teemu Roos

Learning Optimal Causal Graphs with Exact Search Kari Rantanen, Antti Hyttinen, Matti Järvisalo

Making Continuous Time Bayesian Networks More Flexible Manxia Liu, Fabio Stella, Arjen Hommersom, Peter J.F. Lucas

Markov Random Field MAP as Set Partitioning James Cussens

Naive Bayesian Classifiers with Extreme Probability Features Linda C. van der Gaag, Andrea Capotorti

On the Relative Expressiveness of Bayesian and Neural Networks Arthur Choi, Adnan Darwiche

Parallel Probabilistic Inference by Weighted Model Counting Giso H. Dal, Alfons W. Laarman, Peter J.F. Lucas

Parameterized Hardness of Active Inference Nils Donselaar

Privacy Sensitive Construction of Junction Tree Agent Organization for Multiagent Graphical Models Yang Xiang, Abdulrahman Alshememry

Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks Priyank Jaini, Amur Ghose, Pascal Poupart

Representations of Bayesian Networks by Low-Rank Models Petr Tichavský, Jiří Vomlel

Same-Decision Probability: Threshold Robustness and Application to Explanation Silja Renooij

Simple Propagation with Arc-Reversal in Bayesian Networks Anders Madsen, Cory J. Butz, Jhonatan S. Oliveira, André E. Santos

Solving M-Modes in Loopy Graphs Using Tree Decompositions Cong Chen, Changhe Yuan, Ze Ye, Chao Chen

Sparse Learning in Gaussian Chain Graphs for State Space Models Lasse Petersen

Structure Learning for Bayesian Networks over Labeled DAGs Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander

Structure Learning Under Missing Data Alexander Gain, Ilya Shpitser

Unifying DAGs and UGs Jose M. Peña

Who Learns Better Bayesian Network Structures: Constraint-Based, Score-Based or Hybrid Algorithms? Marco Scutari, Catharina Elisabeth Graafland, José Manuel Gutiérrez