Probabilistic Graphical Models

Keyphrases

Publications

2016

Cory J. Butz, André E. dos Santos, Jhonatan de S. Oliveira
Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks. Probabilistic Graphical Models (2016)
Juan Miguel Ogarrio, Peter Spirtes, Joe Ramsey
A Hybrid Causal Search Algorithm for Latent Variable Models. Probabilistic Graphical Models (2016)
Marco Scutari
An Empirical-Bayes Score for Discrete Bayesian Networks. Probabilistic Graphical Models (2016)
Christiane Görgen, Jim Q. Smith
A Differential Approach to Causality in Staged Trees. Probabilistic Graphical Models (2016)
Marco Benjumeda, Concha Bielza, Pedro Larrañaga
Learning Tractable Multidimensional Bayesian Network Classifiers. Probabilistic Graphical Models (2016)
Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Probabilistic Graphical Models (2016)
Denis Deratani Mauá, Fábio Gagliardi Cozman
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks. Probabilistic Graphical Models (2016)
Nicola Di Mauro, Antonio Vergari, Floriana Esposito
Multi-Label Classification with Cutset Networks. Probabilistic Graphical Models (2016)
Marco E. G. V. Cattaneo
Conditional Probability Estimation. Probabilistic Graphical Models (2016)
Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Gavin Brown
Estimating Mutual Information in Under-Reported Variables. Probabilistic Graphical Models (2016)
Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen
d-VMP: Distributed Variational Message Passing. Probabilistic Graphical Models (2016)
Elena Sokolova, Martine Hoogman, Perry Groot, Tom Claassen, Tom Heskes
Computing Lower and Upper Bounds on the Probability of Causal Statements. Probabilistic Graphical Models (2016)
José M. Peña
Learning Acyclic Directed Mixed Graphs from Observations and Interventions. Probabilistic Graphical Models (2016)
Kiran Karra, Lamine Mili
Hybrid Copula Bayesian Networks. Probabilistic Graphical Models (2016)
Jasper De Bock
Reintroducing Credal Networks under Epistemic Irrelevance. Probabilistic Graphical Models (2016)
Yi Tan, Prakash P. Shenoy, Moses W. Chan, Paul M. Romberg
On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification. Probabilistic Graphical Models (2016)
Eunice Yuh-Jie Chen, Arthur Choi, Adnan Darwiche
On Pruning with the MDL Score. Probabilistic Graphical Models (2016)
Nourhene Ettouzi, Philippe Leray, Montassar Ben Messaoud
An Exact Approach to Learning Probabilistic Relational Model. Probabilistic Graphical Models (2016)
Evangelia Kyrimi, William Marsh
A Progressive Explanation of Inference in 'Hybrid' Bayesian Networks for Supporting Clinical Decision Making. Probabilistic Graphical Models (2016)
Martin Plajner, Jirí Vomlel
Student Skill Models in Adaptive Testing. Probabilistic Graphical Models (2016)
Johan Kwisthout
The Parameterized Complexity of Approximate Inference in Bayesian Networks. Probabilistic Graphical Models (2016)
Milan Studený, James Cussens
The Chordal Graph Polytope for Learning Decomposable Models. Probabilistic Graphical Models (2016)
Ross D. Shachter
Decisions and Dependence in Influence Diagrams. Probabilistic Graphical Models (2016)
Fábio Gagliardi Cozman, Denis Deratani Mauá
Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity. Probabilistic Graphical Models (2016)
Pekka Parviainen, Samuel Kaski
Bayesian Networks for Variable Groups. Probabilistic Graphical Models (2016)
Priya Krishnan Sundararajan, Ole J. Mengshoel
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization. Probabilistic Graphical Models (2016)
Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, Anders L. Madsen
On Bayesian Network Inference with Simple Propagation. Probabilistic Graphical Models (2016)
Eva Endres, Thomas Augustin
Statistical Matching of Discrete Data by Bayesian Networks. Probabilistic Graphical Models (2016)
Silja Renooij
Evidence Evaluation: a Study of Likelihoods and Independence. Probabilistic Graphical Models (2016)
Marcus Bendtsen
Regime Aware Learning. Probabilistic Graphical Models (2016)
Yang Xiang, Qian Jiang
Compressing Bayes Net CPTs with Persistent Leaky Causes. Probabilistic Graphical Models (2016)
Janneke H. Bolt
Bayesian Networks: a Combined Tuning Heuristic. Probabilistic Graphical Models (2016)
Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias
Dynamic Sum Product Networks for Tractable Inference on Sequence Data. Probabilistic Graphical Models (2016)
Jidapa Kraisangka, Marek J. Druzdzel
Making Large Cox's Proportional Hazard Models Tractable in Bayesian Networks. Probabilistic Graphical Models (2016)
Eugene Dementiev, Norman E. Fenton
Bayesian Torrent Classification by File Name and Size Only. Probabilistic Graphical Models (2016)
Bence Bolgár, Peter Antal
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences. Probabilistic Graphical Models (2016)
Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart
Online Algorithms for Sum-Product Networks with Continuous Variables. Probabilistic Graphical Models (2016)
Manxia Liu, Arjen Hommersom, Maarten van der Heijden, Peter J. F. Lucas
Learning Parameters of Hybrid Time Bayesian Networks. Probabilistic Graphical Models (2016)
Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. Probabilistic Graphical Models (2016)
Maxime Gasse, Alex Aussem
Identifying the irreducible disjoint factors of a multivariate probability distribution. Probabilistic Graphical Models (2016)
Peter Marx, András Millinghoffer, Gabriella Juhász, Peter Antal
Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease. Probabilistic Graphical Models (2016)
Carlos Morales, Serafín Moral
Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks. Probabilistic Graphical Models (2016)
Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Sicco Verwer, Alexis Linard
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case. Probabilistic Graphical Models (2016)
Ivar Simonsson, Petter Mostad
Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks. Probabilistic Graphical Models (2016)
Daniel Malinsky, Peter Spirtes
Estimating Causal Effects with Ancestral Graph Markov Models. Probabilistic Graphical Models (2016)
Michael Glodek, Georg Layher, Heiko Neumann, Susanne Biundo, Günther Palm
On Stacking Probabilistic Temporal Models with Bidirectional Information Flow. Probabilistic Graphical Models (2016)

volume 52, 2016

Probabilistic Graphical Models - Eighth International Conference, PGM 2016, Lugano, Switzerland, September 6-9, 2016. Proceedings Probabilistic Graphical Models 52 (2016)

2014

volume 8754, 2014

Probabilistic Graphical Models - 7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings Probabilistic Graphical Models 8754 (2014)