Limited Memory Influence Diagrams for Attribute Statistical Process Control with Variable Sample Sizes

Barry R. Cobb; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:1-12

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Relevance for Robust Bayesian Network MAP-Explanations

Silja Renooij; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:13-24

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The Functional LiNGAM

Tianle Yang, Joe Suzuki; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:25-36

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Online Single-Microphone Source Separation using Non-Linear Autoregressive Models

Bart van Erp, Bert de Vries; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:37-48

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Anytime Learning of Sum-Product and Sum-Product-Max Networks

Swaraj Pawar, Prashant Doshi; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:49-60

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Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling

Peter Strong, Jim Q. Smith; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:61-72

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Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets

Marco Scutari, Christopher Marquis, Laura Azzimonti; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:73-84

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Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization

Mariana Vargas Vieyra; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:85-96

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Online Updating of Conditional Linear Gaussian Bayesian Networks

Anders L Madsen, Kristian G Olesen, Frank Jensen, Per Henriksen, Thomas M Larsen, Jørn M Møller; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:97-108

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A Transformational Characterization of Unconditionally Equivalent Bayesian Networks

Alex Markham, Danai Deligeorgaki, Pratik Misra, Liam Solus; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:109-120

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Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound

Kiattikun Chobtham, Anthony C. Constantinou; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:121-132

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Model inclusion lattice of coloured Gaussian graphical models for paired data

Alberto Roverato, Dung Ngoc Nguyen; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:133-144

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Parameterized Completeness Results for Bayesian Inference

Hans L. Bodlaender, Nils Donselaar, Johan Kwisthout; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:145-156

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Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models

Pierre Gillot, Pekka Parviainen; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:157-168

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You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks

Rafael Ballester-Ripoll, Manuele Leonelli; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:169-180

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Scalable Bayesian Network Structure Learning with Splines

Charupriya Sharma, Peter van Beek; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:181-192

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Highly Efficient Structural Learning of Sparse Staged Trees

Manuele Leonelli, Gherardo Varando; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:193-204

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A Reparameterization of Mixtures of Truncated Basis Functions and its Applications

Antonio Salmerón, Helge Langseth, Andrés Masegosa, Thomas D. Nielsen; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:205-216

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Who did it? Identifying the Most Likely Origins of Events

Marcel Gehrke, Ralf Möller, Tanya Braun; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:217-228

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Speeding up approximate MAP by applying domain knowledge about relevant variables

Johan Kwisthout; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:229-240

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A Hybrid Algorithm for Learning Causal Networks using Uncertain Experts’ Knowledge

Christophe Gonzales, Axel Journe, Ahmed Mabrouk; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:241-252

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A Decision Support System to Predict Acute Fish Toxicity

Anders L Madsen, S. Jannicke Moe, Thomas Braunbeck, Kristin A. Connors, Michelle Embry, Kristin Schirmer, Stefan Scholz, Raoul Wolf, Adam Lillicrap; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:253-264

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Recursive autonomy identification-based learning of augmented naive Bayes classifiers

Shouta Sugahara, Wakaba Kishida, Koya Kato, Maomi Ueno; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:265-276

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Learning Noisy-Or Networks with an Application in Linguistics

František Kratochvíl, Václav Kratochvíl, Jiří Vomlel; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:277-288

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Bounding Counterfactuals under Selection Bias

Marco Zaffalon, Alessandro Antonucci, Rafael Cabañas, David Huber, Dario Azzimonti; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:289-300

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The Dual PC Algorithm for Structure Learning

Enrico Giudice, Jack Kuipers, Giusi Moffa; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:301-312

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Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers

Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:313-324

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Explaining Deep Tractable Probabilistic Models: The sum-product network case

Bhagirath Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M Haas, Kristian Kersting, Sriraam Natarajan; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:325-336

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Integrating Bayesian network classifiers to deal with the partial label ranking problem

Juan C. Alfaro, Juan A. Aledo, José A. Gámez; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:337-348

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A Hardware Perspective to Evaluating Probabilistic Circuits

Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy, Lingyun Yao, Martin Trapp, Martin Andraud; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:349-360

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On the rank of 2×2×2 probability tables

Iván Pérez, Jiřı́ Vomlel; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:361-372

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Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling

Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:373-384

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Knowledge transfer for learning subject-specific causal models

Verónica Rodrı́guez-López, Luis Enrique Sucar; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:385-396

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Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection

Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:397-408

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Graphical Representations for Algebraic Constraints of Linear Structural Equations Models

Thijs van Ommen, Mathias Drton; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:409-420

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Causal Discovery and Reinforcement Learning: A Synergistic Integration

Arquı́mides Méndez-Molina, Eduardo F.Morales, L. Enrique Sucar; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:421-432

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Approximate Inference for Stochastic Planning in Factored Spaces

Zhennan Wu, Roni Khardon; Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186:433-444

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