Preface: The 13th International Conference on Probabilistic Graphical Models (PGM 2026)

Gustau Camps-Valls, Manuele Leonelli, Gherardo Varando; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:1-1

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Optimized Priority Scheduling for Faster Scalable Belief Propagation

Abnash Bassi, Gilead Posluns, Mark C. Jeffrey; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:2-17

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Finite Dimensional Approximations of Incentive Functions for Causal Incentive Design Models

Sebastián Bejos, Eduardo F. Morales, Enrique Munoz de Cote, Luis Enrique Sucar; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:18-35

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An AutoML-Powered Architecture for Causal Discovery

Konstantina Biza, Sofia Triantafillou, Ioannis Tsamardinos; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:36-56

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Augmenting Bayesian Networks with Categorical Principal Components

Ashley Bojko, Marie Melı́nová, Jiřı́ Vomlel; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:57-72

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Table-based Probability Trees: a New Hybrid Potential Representation for Probabilistic Inference in Graphical Models

Francisco Bonillo, Andrés Cano, Manuel Gómez-Olmedo, Serafín Moral; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:73-91

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Counterfactual Fairness under Hidden Confounding

Marc Braun, Jose M. Peña, Adel Daoud; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:92-111

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Fast Constraint-Based Structure Learning for Continuous-Time Bayesian Networks

Alessandro Bregoli, Marco Midali, Marco Scutari, Fabio Stella, Alessio Zanga; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:112-126

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Safe Inverse Marginalization in Bayesian Networks

Cory Butz, Alejandro Santoscoy-Rivero, Silja Renooij, Johan Kwisthout; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:127-139

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Selective Indicator Elimination in Arithmetic Circuits for Bipartite Noisy-OR Bayesian Networks

Cory Butz, Alejandro Santoscoy-Rivero, Jiřı́ Vomlel, Anders Madsen; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:140-152

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Accounting for Data Uncertainty in Counterfactual Reasoning

Rafael Cabañas, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:153-166

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Parameterising Gaussian Graphical Models

Jack Storror Carter; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:167-181

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Learning Causal Structure of Time Series using Best Order Score Search

Irene Gema Castillo Mansilla, Urmi Ninad; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:182-209

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Algorithmics for Graphical Separation Criteria

Moisés Chavira-Flores, Sebastian Weichwald, Leonard Henckel; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:210-245

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I-FLOP: Fast Learning of Order and Parents from Interventional Data

Liuting Chen, Alex Markham; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:246-273

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Scope-Restricted Backtracking Counterfactuals

Johan de Aguas, Martin Jullum; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:274-305

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Local Robustness Quantification for Naive Bayes Classifiers and Generative Forests: a General Approach

Adrián Detavernier, Jasper De Bock; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:306-322

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Spectral Sparsification of Laplacian-Constrained Gaussian and Hüsler–Reiss Graphical Models

Ignacio Echave-Sustaeta Rodrı́guez, Aida Abiad, Frank Röttger; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:323-345

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How Does Bayesian Causal Discovery Fail: Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding

Debargha Ghosh, Silja Renooij, Anna V. Kononova; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:346-362

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Using P&IDs and Process Data To Construct Bayesian Networks For Anomaly Detection

Jakob Ø. Hansen, Anders Læsø Madsen, Thomas Dyhre Nielsen, Joseph Mietkiewicz, Gabriele Baldissone, Micaela Demichela; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:363-378

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A Comparative Review of Probabilistic Inference for Timescale Graphical Event Models

El Mokhtar Hribach, Julien Blanchard, Philippe Leray; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:379-391

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What to Check Next? Bayesian Networks and Rollout-Based Lookahead for Quicker Inspections

Sebastiaan J. J. Jans, Thijs van Ommen, Ad Feelders, Cor Veenman; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:392-407

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Differentiable Structural EM for Explicit-Latent Linear–Gaussian DAGs

Mohammad Ali Javidian, R. Mitchell Parry; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:408-446

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LLM-Augmented Causal Discovery: Probabilistic Fusion of Edge Existence and Orientation

Neville K. Kitson, Anthony C. Constantinou; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:447-472

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Bayesian estimation of causal effects in Bayesian networks with local structure

Vera Kvisgaard, Johan Pensar; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:473-496

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On the Detection of Commutative Factors in Factor Graphs: Necessary and Sufficient Conditions

Malte Luttermann, Ralf Möller, Marcel Gehrke; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:497-522

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Hierarchically Coupled Gaussian Bayesian Networks

Chang Ma, Marco Grzegorczyk; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:523-544

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A Bayesian Network Approach to Earth Fault Localization in Medium Voltage Electricity Grids

Anders L Madsen, Somesh Bhattacharya, Hans-Peter Schwefel, Rasmus L Olsen; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:545-558

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Causal Modelling of Support Interventions for Student Competency Assessment

Francesca Mangili, Alessandro Antonucci, Rafael Cabañas de Paz; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:559-574

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Semiparametric Inference for Half-Trek Estimators in Linear Structural Equation Models

Leopold Mareis, Nils Sturma, Mathias Drton; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:575-598

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Neuro-Causal Factor Analysis

Alex Markham, Mingyu Liu, Bryon Aragam, Liam Solus; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:599-628

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Gradient-Based Fine-Tuning of Expert Bayesian Network Classifiers: Application in Forensic Porcine Wound Age Assessment

Joseph Mietkiewicz, Anders L Madsen, Thomas Dyhre Nielsen, Cecilie Bækgård, Henrik Elvang Jensen, Kristiane Barington; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:629-645

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LOCO-FL: Scaling and Reference Choice for Bayesian Structural Analysis of Between-Center Heterogeneity in Federated Learning with Markov Boundaries

András Millinghoffer, Júlia Kisida, Andrea Valek, Miklós Szabó, Péter Antal; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:646-662

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Testable Implications of Causal Graphs in the Presence of Measurement Error

Karthika Mohan, Samuel Zink; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:663-676

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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression

Wouter W. L. Nuijten, Esther G. van Pelt, Albert Podusenko, İsmail Şenöz, Wouter M. Kouw; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:677-696

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Tensor Train Decomposition for BN2A Structure Learning

Iván Pérez, Jiřı́ Vomlel, Patrı́cia Martinková; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:697-710

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Bayesian Network MPE via LLM-Compiled Semantic Maximizing Circuits

Victor H. S. S. Ragazzi, Jhonatan S. Oliveira, Cory Butz, Leonardo Bonato Felix; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:711-724

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BNqMark: Bayesian-Network Inference in Large Language Models

Fernando Rodriguez, Bojan Mihaljević; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:725-757

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Partial Identification under Causal Orders by Linear Programming

Eric Rossetto, Alessandro Antonucci; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:758-779

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Shapeshifter: A Dynamic Graph-Restructuring Algorithm for Improved Inference in Loopy-Structured PGMs

Katerine M. Sadie, Johan A. du Preez, Willie Brink; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:780-796

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Parameter Sensitivity Analysis in Mixtures of Polynomials

Ángel Tomás Sáez-Ruiz, Rafael Rumı́, Ana D. Maldonado; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:797-817

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Forward sampling for State Variable Graphical Event Models with Markovian and piecewise constant dependencies

Moustafa Said Hawchar, Philippe Leray, Yanis Ouerdani, Pierre Jannin; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:818-834

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Non-Symmetric Information Operators in GMRFs for PDE Inference

Yumeng Shi, Concha Bielza, Pedro Larrañaga; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:835-849

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Predicting the Risk of Vehicle–Cyclist Crashes in Urban Intersections Using Bayesian Networks

Kranthi Kumar Talluri, Anders L Madsen, Galia Weidl, Christer Ahlström, Johan Olstam; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:850-863

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Federated Causal Discovery via Regression-Directed Cumulants

Pablo Torrijos, Fabio Stella, José A. Gámez, José M. Puerta; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:864-880

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Partially Ordering Graphical Models with Latent Confounders by their Equality Constraints

Thijs van Ommen, W. J. Merijn Roelfsema; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:881-894

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On Computing Total Variation Distance between Markov Logic Networks

Zixiang Xiong, Peter Jung, Qiaolan Meng, Yuanhong Wang, Ondřej Kuželka, Yuyi Wang; Proceedings of the 13th International Conference on Probabilistic Graphical Models, PMLR 343:895-910

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