Bayesian Networks

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Overview

A Bayesian network uses a directed acyclic graph and local conditional probability models to represent how variables depend on one another, supporting tasks such as diagnosis, prediction, and information gathering. Researchers learn graphs from data using score-based and constraint-based search, often adding expert knowledge or priors, while inference methods range from exact algorithms to sampling and neural approximations. Applications span causal discovery, clinical modeling, time series, and synthetic data generation, with growing work combining networks with language models and differentiable mechanisms. Key challenges include scaling inference and structure search, distinguishing causal direction from observational association, and handling latent confounding, sparse data, and uncertain or imperfect prior knowledge.

Latest papers

CardsList

47 papers6 papers in the last four weeks, down 25% on the four weeks before. 0.0% of all new papers.

  1. Dirichlet Process Mixtures within Semiparametric Bayesian Networks: A Novel Conditional Density Estimation Approach

    Oct 26, 2026Victor Alejandre, Pedro Larrañaga, Concha BielzaBayesian NetworksConditional Distribution Estimation

    Computational Intelligence Group Departamento de Inteligencia Artificial Universidad Politécnica de Madrid Campus de Montegancedo, Boadilla del Monte 28660 Madrid, Spain

  2. Semi-Linear Gaussian Bayesian Networks: Enhancing Flexibility in Node Dependencies via penalized B-Splines

    Oct 22, 2026Aitor Oviedo-Madrid, Mabel Morales-Otero, Jose Gonzalez-Gomariz +1Bayesian Network Structure LearningBayesian Networks

    Institute of Data Science and Artificial Intelligence (DATAI), University of Navarra, Pamplona, Spain · TECNUN School of Engineering, University of Navarra, San Sebastián, Spain

  3. Generalizing Metropolis-Hastings for DAG Sampling

    Oct 21, 2026Daniele Nikzad, Mikko KoivistoBayesian Network Structure LearningMarkov Chain Monte Carlo

    Department of Computer Science, University of Helsinki, Helsinki, FI-00014, Finland

  4. Trail-Weighted Influence Scores for Approximate Outcome Prediction in Bayesian Networks

    Oct 19, 2026Sahil Kumar Rajput, Randhir KumarBayesian NetworksBayesian Inference

  5. Neural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty

    Oct 12, 2026Giovanni Briglia, Marco Lippi, Stefano Mariani +1Bayesian NetworksEfficient Neural Network Inference

    University of Modena and Reggio Emilia, Reggio Emilia, Italy · University of Florence, Florence, Italy

  6. Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

    Oct 6, 2026Upala Junaida Islam, Abdelmonem Elrefaey, Rong PanScore-Based Causal DiscoveryBayesian Network Structure Learning

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

  7. CreateScore: Domain-Theory-Informed Bayesian Routing for LLM-Based CV Screening

    Oct 2, 2026Rupsa RoyLLM RoutingLLM Evaluation

    Independent Researcher, MSc in Statistics (2019-21), National University of Singapore (NUS)

  8. ConsultMind:Towards Automated Diagnostic Consultation via Uncertainty-Aware Reasoning

    Sep 25, 2026Xiao Sun, Yuming Yang, Yun Chen +9Medical DiagnosisClinical Decision-Making

    College of Computer Science, Chongqing University · College of Computer Science, Hunan University · Institute of Automation, Chinese Academy of Sciences +5

  9. PRISM-BN: A Controlled Corpus and Benchmark for Text-to-Parameterized Bayesian Network Extraction

    Sep 18, 2026Amartya Bhattacharya, Nikhil Singh, Neeti Pokhriyal +1Bayesian Networks

    Dartmouth College · RAND Corporation

  10. ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMs

    Sep 14, 2026Jackson Hassell, Chen Shen, Estevam HruschkaGraph Structure LearningBayesian Network Structure Learning

    Megagon Labs

  11. 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

  12. Tensor Network Moral Graph Recovery of Discrete Probability Distributions

    Sep 8, 2026Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2Tensor NetworksGraph Structure Learning

    Heisenberg Research Center (Munich), Huawei Technologies Duesseldorf GmbH, Germany · Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain

  13. LEBGen: An LLM-Enhanced Bayesian Network Framework for Few-Shot Travel Survey Data Generation

    Sep 8, 2026Zijian Shen, Bin Zhou, Jiguang Wang +2Bayesian NetworksSynthetic Data Generation

    Department of Civil Engineering, The University of Hong Kong · Department of Urban Planning and Design, The University of Hong Kong

  14. Deep belief networks are exact

    Sep 4, 2026Gleb SmirnovNeural Network Approximation TheoryBayesian Networks

  15. Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge Pruning

    Sep 3, 2026Pablo Torrijos, José A. Gámez, José M. Puerta +1Bayesian NetworksGenetic Algorithms

    Universidad de Castilla-La Mancha Departamento de Sistemas Informáticos, Albacete, Spain · Universidad de Castilla-La Mancha Departamento de Matemáticas, Albacete, Spain

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

    Aug 19, 2026Neville K. Kitson, Anthony ConstantinouBayesian Network Structure LearningCausal Discovery

    Machine Intelligence and Decision Systems (MInDS) Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom, E1 4NS.

  17. The Cost of Binarizing Survival Outcomes in Clinical Prognostic Modeling

    Aug 4, 2026Shashank Yadav, David M. Routman, Andrew Y. K. FoongCancer Survival PredictionBayesian Networks

    Department of Radiation Oncology Mayo Clinic, Rochester, MN, USA 55905

  18. LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation

    Aug 3, 2026Zijian Shen, Taijie Chen, Bin Zhou +2Bayesian Network Structure LearningBayesian Networks

    Department of Civil Engineering, The University of Hong Kong

  19. Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions

    Jul 29, 2026Shuo-Chieh Huang, Chien-Ming Chi, Jau-er ChenBayesian NetworksDensity 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

  20. 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

  21. Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks

    Jul 28, 2026Bart Custers, Koorosh AslansefatMulti-Agent LLM SystemsUncertainty Quantification

    University of Hull, Hull HU6 7RX, UK

  22. 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 ModelsBayesian Networks

    Department of Information and Computing Sciences, Utrecht University · Leiden Institute of Advanced Computer Science, Leiden University

  23. Decomposition for Bayesian Networks: Local and Parallel Inference

    Jul 6, 2026Pei Heng, Xinyi Hu, Yi SunParameter EstimationBayesian Networks

    Institute of Statistics and Data Science, Xinjiang University of Finance and Economics, Urumqi, China

  24. Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression

    Jun 14, 2026Nguyen Linh Dan LeCausal Effect EstimationStructural Causal Models

    Department of Biomedical Engineering The University of Melbourne, Melbourne, Australia

  25. KG-SoftMAP: Soft Knowledge-Graph Priors for Bayesian Network Structure Learning from Sparse Discrete Data

    Jun 9, 2026Guoliang Xu, James E. CorterGraph Structure LearningBayesian Network Structure Learning

    Columbia University

  26. Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation

    Jun 5, 2026Manuele LeonelliExplainable Artificial IntelligenceAI Accountability

    School of Science and Technology, IE University, Madrid, Spain

  27. Causal Atlases from Entropic Inference: Bayesian Networks beyond Optimal DAGs

    Jun 4, 2026Hazhir Aliahmadi, Irina Babayan, Greg van AndersStructural Causal ModelsBayesian Networks

    Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston ON, Canada

  28. LMT: A Bayesian Framework for Causal Discovery from Textual Alarm Records in Manufacturing Systems

    Jun 3, 2026Xiaofeng Xiao, Jianhong Chen, Qiuzhuang Sun +2Bayesian NetworksCausal 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

  29. Extending Causal Metamodeling to a non-Markovian Queue

    May 30, 2026Pracheta Amaranath, Anant Bhide, David Jensen +1Surrogate ModelingBayesian Networks

    Manning College of Information and Computer Sciences, University of Massachusetts Amherst, MA, USA

  30. 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 NetworksMulti-Objective Evolutionary Optimization

    Leiden University Medical Center · Centrum Wiskunde & Informatica