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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-05-29 · via Proceedings of Machine Learning Research

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Volume 246: International Conference on Probabilistic Graphical Models, 11-13 September 2024, De Lindenberg, Nijmegen, the Netherlands

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Editors: Johan Kwisthout, Silja Renooij

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Preface

; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:i-iv

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Alternative Measures of Direct and Indirect Effects

Jose M. Peña; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:1-19

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$ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows

Sourabh Balgi, Jose M. Peña, Adel Daoud; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:20-37

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Efficient Detection of Commutative Factors in Factor Graphs

Malte Luttermann, Johann Machemer, Marcel Gehrke; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:38-56

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LIMID Quality Control Models for Increasing Failure Rate Processes

Barry R. Cobb; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:57-69

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On the Unlikelihood of D-Separation

Itai Feigenbaum, Devansh Arpit, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Huan Wang, Caiming Xiong, Silvio Savarese; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:70-92

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Fast Arc-Reversal

Cory J. Butz, Anders L. Madsen, Jhonatan S. Oliveira; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:93-105

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AutoCD: Automated Machine Learning for Causal Discovery Algorithms

Gerlise Chan, Tom Claassen, Holger H. Hoos, Tom Heskes, Mitra Baratchi; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:106-132

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Modelling Shared Decision Making Interactions using Influence Diagrams

Zeliha Yildirim, Barbaros Yet; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:133-146

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Eliminating Variable Order Instability in Greedy Score-Based Structure Learning

Neville K Kitson, Anthony C Constantinou; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:147-163

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Counterfactually-Equivalent Structural Causal Modelling Using Causal Graphical Normalizing Flows

Sourabh Balgi, Jose M. Peña, Adel Daoud; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:164-181

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Context-Specific Refinements of Bayesian Network Classifiers

Manuele Leonelli, Gherardo Varando; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:182-198

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Latent Gaussian Graphical Models with Golazo Penalty

Ignacio Echave-Sustaeta Rodríguez, Frank Röttger; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:199-212

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Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity

David Strieder, Mathias Drton; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:213-230

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Learning Staged Trees from Incomplete Data

Jack Storror Carter, Manuele Leonelli, Eva Riccomagno, Gherardo Varando; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:231-252

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Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models

Yurou Liang, Oleksandr Zadorozhnyi, Mathias Drton; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:253-272

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Soft Learning Probabilistic Circuits

Soroush Ghandi, Benjamin Quost, Cassio de Campos; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:273-294

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Q-conjugate Message Passing for Efficient Bayesian Inference

Mykola Lukashchuk, İsmail Şenöz, Bert de Vries; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:295-311

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Learning Causal Markov Boundaries with Mixed Observational and Experimental Data

Konstantina Lelova, Gregory F. Cooper, Sofia Triantafillou; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:312-326

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Geometric No-U-Turn Samplers: Concepts and Evaluation

Bernardo Williams, Hanlin Yu, Marcelo Hartmann, Arto Klami; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:327-347

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A Divide and Conquer Approach for Solving Structural Causal Models

Anna Rodum Bjøru, Rafael Cabañas, Helge Langseth, Antonio Salmerón; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:348-360

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Balancing Computational Cost and Accuracy in Inference of Continuous Bayesian Networks

Maarten C. Vonk, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, Alfons Laarman, Anna V. Kononova; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:361-381

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Causal Structure Learning With Momentum: Sampling Distributions Over Markov Equivalence Classes

Moritz Schauer, Marcel Wienöbst; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:382-400

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Enhancing Bayesian Networks with Psychometric Models

I. Pérez, J. Vomlel; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:401-414

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Multi-objective Counterfactuals in Bayesian Classifiers with Estimation of Distribution Algorithms

Daniel Zaragoza-Pellicer, Concha Bielza, Pedro Larrañaga; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:415-426

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An Adaptive Implicit Hitting Set Algorithm for MAP and MPE Inference

Aleksandra Petrova, Javier Larrosa, Emma Rollon; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:427-437

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Exploring Argument Mining and Bayesian Networks for Assessing Topics for City Project Proposals

Galia Weidl, Stefan Berres, Anders L. Madsen, Johannes Daxenberger, Annegret Aulbach; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:438-451

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$Ψ$net: Efficient Causal Modeling at Scale

Florian Peter Busch, Moritz Willig, Jonas Seng, Kristian Kersting, Devendra Singh Dhami; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:452-469

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Uncovering Relationships using Bayesian Networks: A Case Study on Conspiracy Theories

Jiřı́ Vomlel, Aleš Kuběna, Martin Šmı́d, Josefina Weinerova; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:470-485

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Time–Approximation Trade-Offs for Learning Bayesian Networks

Madhumita Kundu, Pekka Parviainen, Saket Saurabh; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:486-497

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Estimating Bounds on Causal Effects Considering Unmeasured Common Causes

Sebastian Bejos, Luis Enrique Sucar, Eduardo F. Morales; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:498-514

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Serving MPE Queries on Tensor Networks by Computing Derivatives

Maurice Wenig, Hanno Barschel, Joachim Giesen, Andreas Goral, Mark Blacher; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:515-527

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Cauchy Graphical Models

Taurai Muvunza, Yang Li, Kuruoglu Ercan Engin; Proceedings of The 12th International Conference on Probabilistic Graphical Models, PMLR 246:528-542

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