Bayesian Networks

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4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Directional Evidence Guided Search-Space Reduction for Exact DAG Learning
Oct 6, 2026Upala Junaida Islam, Abdelmonem Elrefaey, Rong PanCausal Discovery Causal Structure Learning
School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA.
ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMs
Sep 14, 2026Jackson Hassell, Chen Shen, Estevam HruschkaGraph Structure Learning Bayesian Networks
Megagon Labs
Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms
Sep 9, 2026Pablo Torrijos, José A. Gámez, José M. PuertaBayesian Networks
Instituto de Investigaci´on en Inform´atica de Albacete (I3A). Universidad de Castilla-La Mancha. Albacete, 02071, Spain · Departamento de Sistemas Inform´aticos. Universidad de Castilla-La Mancha. Albacete, 02071, Spain
Tensor Network Moral Graph Recovery of Discrete Probability Distributions
Sep 8, 2026Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2Tensor Networks Graph Structure Learning
Heisenberg Research Center (Munich), Huawei Technologies Duesseldorf GmbH, Germany · Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain
LEBGen: An LLM-Enhanced Bayesian Network Framework for Few-Shot Travel Survey Data Generation
Sep 8, 2026Zijian Shen, Bin Zhou, Jiguang Wang +2Bayesian Networks Synthetic Data Generation
Department of Civil Engineering, The University of Hong Kong · Department of Urban Planning and Design, The University of Hong Kong
Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge Pruning
Sep 3, 2026Pablo Torrijos, José A. Gámez, José M. Puerta +1Bayesian Networks Genetic Algorithms
Universidad de Castilla-La Mancha Departamento de Sistemas Informáticos, Albacete, Spain · Universidad de Castilla-La Mancha Departamento de Matemáticas, Albacete, Spain
The Cost of Binarizing Survival Outcomes in Clinical Prognostic Modeling
Aug 4, 2026Shashank Yadav, David M. Routman, Andrew Y. K. FoongCancer Survival Prediction Bayesian Networks
Department of Radiation Oncology Mayo Clinic, Rochester, MN, USA 55905
LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation
Aug 3, 2026Zijian Shen, Taijie Chen, Bin Zhou +2Bayesian Networks Synthetic Tabular Data Generation
Department of Civil Engineering, The University of Hong Kong
Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions
Jul 29, 2026Shuo-Chieh Huang, Chien-Ming Chi, Jau-er ChenBayesian Networks Density Estimation
Department of Statistics, Rutgers University, Piscataway, NJ, U.S.A. · Institute of Statistical Science, Academia Sinica, Taipei, Taiwan · School of Political Science and Economics, National Taiwan University, Taipei, Taiwan
High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption
Jul 29, 2026Loong Kuan Lee, Ragavi Krishnamoorthy, Nico PiatkowskiBayesian Networks
Hybrid Intelligence, Fraunhofer IAIS, Sankt Augustin, Germany
Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks
Jul 28, 2026Bart Custers, Koorosh AslansefatMulti-Agent LLM Systems Uncertainty Quantification
University of Hull, Hull HU6 7RX, UK
How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding
Jul 10, 2026Debargha Ghosh, Silja Renooij, Anna V. KononovaStructural Causal Models Bayesian Networks
Department of Information and Computing Sciences, Utrecht University · Leiden Institute of Advanced Computer Science, Leiden University
Decomposition for Bayesian Networks: Local and Parallel Inference
Jul 6, 2026Pei Heng, Xinyi Hu, Yi SunParameter Estimation Bayesian Networks
Institute of Statistics and Data Science, Xinjiang University of Finance and Economics, Urumqi, China
Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression
Jun 14, 2026Nguyen Linh Dan LeCausal Effect Estimation Structural Causal Models
Department of Biomedical Engineering The University of Melbourne, Melbourne, Australia
KG-SoftMAP: Soft Knowledge-Graph Priors for Bayesian Network Structure Learning from Sparse Discrete Data
Jun 9, 2026Guoliang Xu, James E. CorterGraph Structure Learning Bayesian Networks
Columbia University
Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation
Jun 5, 2026Manuele LeonelliExplainable Artificial Intelligence AI Accountability
School of Science and Technology, IE University, Madrid, Spain
Causal Atlases from Entropic Inference: Bayesian Networks beyond Optimal DAGs
Jun 4, 2026Hazhir Aliahmadi, Irina Babayan, Greg van AndersStructural Causal Models Bayesian Networks
Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston ON, Canada
LMT: A Bayesian Framework for Causal Discovery from Textual Alarm Records in Manufacturing Systems
Jun 3, 2026Xiaofeng Xiao, Jianhong Chen, Qiuzhuang Sun +2Bayesian Networks Causal Discovery
Department of Mechanical & Industrial Engineering, Northeastern University, Boston, MA, USA · College of Integrative Studies, Singapore Management University, Singapore · Department of Industrial Engineering and Management Sciences, Department of Mechanical Engineering, Northwestern University, IL, USA
Extending Causal Metamodeling to a non-Markovian Queue
May 30, 2026Pracheta Amaranath, Anant Bhide, David Jensen +1Surrogate Modeling Bayesian Networks
Manning College of Information and Computer Sciences, University of Massachusetts Amherst, MA, USA
Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data
May 27, 2026Damy M. F. Ha, Thalea Schlender, Yvette M. van der Linden +2Bayesian Networks Multi-Objective Evolutionary Optimization
Leiden University Medical Center · Centrum Wiskunde & Informatica
Iterative Causal Discovery: Per-Edge Impossibility Certificates, Tier-Aware Oracle Queries, and the $1+K$ Lower Bound
May 26, 2026Eichi UeharaBayesian Networks Causal Discovery
aflo, Inc., Tokyo, Japan
Bayesian Networks for Path-Based Sensors: Gathering Information and Path Planning in Communication Denied Environments
May 15, 2026Alkesh K. Srivastava, George P. Kontoudis, Donald Sofge +1Bayesian Networks Informative Path Planning
University of Maryland, College Park, MD, US. · Temple University, Philadelphia, PA, US. · Colorado School of Mines, Golden, CO, US. +1
ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models
May 11, 2026Wentao Qiu, Guanran Luo, Zhongquan Jian +3Abductive Reasoning Bayesian Networks
School of Informatics, Xiamen University, Xiamen, China · School of Computer and Data Science, Minjiang University, Fuzhou, China · School of Film, Xiamen University, Xiamen, China +2
Free Energy Manifold: Score-Based Inference for Hybrid Bayesian Networks
May 11, 2026Cheol Young Park, Shou MatsumotoBayesian Networks Energy-Based Models
ATOS Co., Ltd., 273, Digital-ro, Guro-gu, Seoul, 08381, Republic of Korea · C5I Center, George Mason University, Fairfax, VA 22030, USA
Exact and Approximate Algorithms for Polytree Learning
May 5, 2026Juha Harviainen, Frank Sommer, Manuel SorgeGraph Structure Learning Bayesian Networks
Department of Computer Science, University of Helsinki, Helsinki, Finland · Institute of Computer Science, Friedrich-Schiller Universität Jena, Jena, Germany · Institute of Logic and Computation, TU Wien, Vienna, Austria
Learning Causal Structure of Time Series using Best Order Score Search
Mar 5, 2026Irene Gema Castillo Mansilla, Urmi NinadTime-Series Causal Discovery Bayesian Networks
University of Potsdam, Potsdam, Germany · Department of Computer Science, University of Potsdam, Potsdam, Germany
Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization
May 21, 2025Aliakbar Nafar, Kristen Brent Venable, Zijun Cui +1Bayesian Networks Probabilistic Graphical Models
Michigan State University · Florida Institute for Human and Machine Cognition (IHMC) University of West Florida

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

Upala Junaida Islam, Abdelmonem Elrefaey, Rong Pan

School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA.

Causal Discovery Causal Structure Learning Bayesian Networks

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Learning a directed acyclic graph (DAG) from observational data is a challenging combinatorial problem due to the exponential growth in the number of candidate parent-set configurations. Existing exact score-based methods often require computationally intensive combinatorial search, whereas constraint-based methods can become unreliable or computationally demanding as graph size and conditioning-set complexity increase. We develop a non-parametric hybrid framework, referred to as DECO (Directional Evidence-guided Configuration Optimization), that extracts dependency and directional evidence from observation data to construct admissible parent sets prior to exact optimization. It reduces the optimization search space by eliminating empirically unsupported parent configurations while preserving flexibility for all plausible edge orientations. Theoretical analysis establishes an exponential reduction in the admissible parent-set configuration space and quantifies how bounded edge-level omission affects the probability of retaining the true parent structure. Experiments on benchmark Bayesian networks and synthetic discrete and continuous DAGs demonstrate substantial search-space reduction while achieving competitive structure-recovery performance, with favorable structural Hamming distance across many evaluated settings. These results show that directional evidence can provide an effective preprocessing mechanism for reducing the computational burden of exact DAG learning without requiring a fixed parametric structural~model.

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