PGM 2022

37 papers

Approximate Inference for Stochastic Planning in Factored Spaces

ZHENNAN WU, Roni Khardon

Causal Discovery and Reinforcement Learning: A Synergistic Integration

Arquı́mides Méndez-Molina, Eduardo F.Morales, L. Enrique Sucar

Graphical Representations for Algebraic Constraints of Linear Structural Equations Models

Thijs van Ommen, Mathias Drton

Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection

Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga

Knowledge transfer for learning subject-specific causal models

Verónica Rodrı́guez-López, Luis Enrique Sucar

Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling

Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza

On the rank of 2×2×2 probability tables

Iván Pérez, Jiřı́ Vomlel

A Hardware Perspective to Evaluating Probabilistic Circuits

Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy, Lingyun Yao, Martin Trapp

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

Juan C. Alfaro, Juan A. Aledo, José A. Gámez

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

Bhagirath Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M Haas, Kristian Kersting

Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers

Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella

The Dual PC Algorithm for Structure Learning

Enrico Giudice, Jack Kuipers, Giusi Moffa

Bounding Counterfactuals under Selection Bias

Marco Zaffalon, Alessandro Antonucci, Rafael Cabañas, David Huber, Dario Azzimonti

Learning Noisy-Or Networks with an Application in Linguistics

Frantisek Kratochvil, Václav Kratochvíl, Jiří Vomlel

Recursive autonomy identification-based learning of augmented naive Bayes classifiers

Shouta Sugahara, Wakaba Kishida, Koya Kato, Maomi Ueno

A Decision Support System to Predict Acute Fish Toxicity

Anders L Madsen, S. Jannicke Moe, Thomas Braunbeck, Kristin A. Connors, Michelle Embry

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

Christophe Gonzales, Axel Journe, Ahmed Mabrouk

Speeding up approximate MAP by applying domain knowledge about relevant variables

Johan Kwisthout

Who did it? Identifying the Most Likely Origins of Events

Marcel Gehrke, Ralf Möller, Tanya Braun

A Reparameterization of Mixtures of Truncated Basis Functions and its Applications

Antonio Salmerón, Helge Langseth, Andres Masegosa, Thomas D. Nielsen

Highly Efficient Structural Learning of Sparse Staged Trees

Manuele Leonelli, Gherardo Varando

Scalable Bayesian Network Structure Learning with Splines

Charupriya Sharma, Peter van Beek

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

Rafael Ballester-Ripoll, Manuele Leonelli

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

Pierre Gillot, Pekka Parviainen

Parameterized Completeness Results for Bayesian Inference

Hans L. Bodlaender, Nils Donselaar, Johan Kwisthout

Model inclusion lattice of coloured Gaussian graphical models for paired data

Alberto Roverato, Dung Ngoc Nguyen

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

Kiattikun Chobtham, Anthony C. Constantinou

A Transformational Characterization of Unconditionally Equivalent Bayesian Networks

Alex Markham, Danai Deligeorgaki, Pratik Misra, Liam Solus

Online Updating of Conditional Linear Gaussian Bayesian Networks

Anders L Madsen, Kristian G Olesen, Frank Jensen, Per Henriksen, Thomas M Larsen

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

Mariana Vargas Vieyra

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

Marco Scutari, Christopher Marquis, Laura Azzimonti

Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling

Peter Strong, Jim Q. Smith

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

Swaraj Pawar, Prashant Doshi

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

Bart van Erp, Bert de Vries

The Functional LiNGAM

Tianle Yang, Joe Suzuki

Relevance for Robust Bayesian Network MAP-Explanations

Silja Renooij

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

Barry R. Cobb