PGM

Publications

2022

Alex Markham, Danai Deligeorgaki, Pratik Misra, Liam Solus
A Transformational Characterization of Unconditionally Equivalent Bayesian Networks. PGM (2022)
Christophe Gonzales, Axel Journe, Ahmed Mabrouk
A Hybrid Algorithm for Learning Causal Networks using Uncertain Experts' Knowledge. PGM (2022)
Arquímides Méndez-Molina, Eduardo F. Morales, Luis Enrique Sucar
Causal Discovery and Reinforcement Learning: A Synergistic Integration. PGM (2022)
Zhennan Wu, Roni Khardon
Approximate Inference for Stochastic Planning in Factored Spaces. PGM (2022)
Juan C. Alfaro, Juan A. Aledo, José A. Gámez
Integrating Bayesian network classifiers to deal with the partial label ranking problem. PGM (2022)
Marcel Gehrke, Ralf Möller, Tanya Braun
Who did it? Identifying the Most Likely Origins of Events. PGM (2022)
Anders L. Madsen, S. Jannicke Moe, Thomas Braunbeck, Kristin A. Connors, Michelle Embry, Kristin Schirmer, Stefan Scholz, Raoul Wolf, Adam A. Lillicrap
A Decision Support System to Predict Acute Fish Toxicity. PGM (2022)
Rafael Ballester-Ripoll, Manuele Leonelli
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks. PGM (2022)
Manuele Leonelli, Gherardo Varando
Highly Efficient Structural Learning of Sparse Staged Trees. PGM (2022)
Enrico Giudice, Jack Kuipers, Giusi Moffa
The Dual PC Algorithm for Structure Learning. PGM (2022)
Iván Pérez, Jirí Vomlel
On the rank of 2×2×2 probability tables. PGM (2022)
Charupriya Sharma, Peter van Beek
Scalable Bayesian Network Structure Learning with Splines. PGM (2022)
Hans L. Bodlaender, Nils Donselaar, Johan Kwisthout
Parameterized Completeness Results for Bayesian Inference. PGM (2022)
Kiattikun Chobtham, Anthony C. Constantinou
Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound. PGM (2022)
Silja Renooij
Relevance for Robust Bayesian Network MAP-Explanations. PGM (2022)
Barry R. Cobb
Limited Memory Influence Diagrams for Attribute Statistical Process Control with Variable Sample Sizes. PGM (2022)
Johan Kwisthout
Speeding up approximate MAP by applying domain knowledge about relevant variables. PGM (2022)
Swaraj Pawar, Prashant Doshi
Anytime Learning of Sum-Product and Sum-Product-Max Networks. PGM (2022)
Bart van Erp, Bert de Vries
Online Single-Microphone Source Separation using Non-Linear Autoregressive Models. PGM (2022)
Shouta Sugahara, Wakaba Kishida, Koya Kato, Maomi Ueno
Recursive autonomy identification-based learning of augmented naive Bayes classifiers. PGM (2022)
Anders L. Madsen, Kristian G. Olesen, Frank Jensen, Per Henriksen, Thomas Mulvad Larsen, Jørn Munkhof Møller
Online Updating of Conditional Linear Gaussian Bayesian Networks. PGM (2022)
Peter Strong, Jim Q. Smith
Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling. PGM (2022)
Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan
Explaining Deep Tractable Probabilistic Models: The sum-product network case. PGM (2022)
Marco Zaffalon, Alessandro Antonucci, Rafael Cabañas, David Huber, Dario Azzimonti
Bounding Counterfactuals under Selection Bias. PGM (2022)
Mariana Vargas Vieyra
Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization. PGM (2022)
Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy, Lingyun Yao, Martin Trapp, Martin Andraud
A Hardware Perspective to Evaluating Probabilistic Circuits. PGM (2022)
Marco Scutari, Christopher Marquis, Laura Azzimonti
Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets. PGM (2022)
Tianle Yang, Joe Suzuki
The Functional LiNGAM. PGM (2022)
Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection. PGM (2022)
Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling. PGM (2022)
Frantisek Kratochvíl, Václav Kratochvíl, Jirí Vomlel
Learning Noisy-Or Networks with an Application in Linguistics. PGM (2022)
Alberto Roverato, Dung Ngoc Nguyen
Model inclusion lattice of coloured Gaussian graphical models for paired data. PGM (2022)
Pierre Gillot, Pekka Parviainen
Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models. PGM (2022)
Antonio Salmerón, Helge Langseth, Andrés R. Masegosa, Thomas D. Nielsen
A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. PGM (2022)
Thijs van Ommen, Mathias Drton
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models. PGM (2022)
Verónica Rodríguez-López, Luis Enrique Sucar
Knowledge transfer for learning subject-specific causal models. PGM (2022)
Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers. PGM (2022)

volume 186, 2022

International Conference on Probabilistic Graphical Models, PGM 2022, 5-7 October 2022, Almería, Spain. PGM 186 (2022)

2020

volume 138, 2020

International Conference on Probabilistic Graphical Models, PGM 2020, 23-25 September 2020, Aalborg, Hotel Comwell Rebild Bakker, Skørping, Denmark. PGM 138 (2020)