mlsanityData to 7 Oct 2026

Data Analysis with Bayesian Networks: A Bootstrap Approach

arXiv 1301.6695 ↗First posted 23 Jan 2013cs.LG cs.AI stat.MLcited by 31

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Abstract (arXiv)

In recent years there has been significant progress in algorithms and methods for inducing Bayesian networks from data. However, in complex data analysis problems, we need to go beyond being satisfied with inducing networks with high scores. We need to provide confidence measures on features of these networks: Is the existence of an edge between two nodes warranted? Is the Markov blanket of a given node robust? Can we say something about the ordering of the variables? We should be able to address these questions, even when the amount of data is not enough to induce a high scoring network. In this paper we propose Efron's Bootstrap as a computationally efficient approach for answering these questions. In addition, we propose to use these confidence measures to induce better structures from the data, and to detect the presence of latent variables.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jan 2013.

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Citing papers per year: 2021: 2; 2022: 8; 2023: 8; 2024: 5; 2025: 3; 2026: 5.

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  3. 2022Amortized Inference for Causal Structure Learningcited by 89
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  12. 2022Membership Inference Attacks and Generalization: A Causal Perspectivecited by 17
19 more
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  5. 2024Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)cited by 6
  6. 2024Challenges and Considerations in the Evaluation of Bayesian Causal Discoverycited by 5
  7. 2023A Bayesian Take on Gaussian Process Networkscited by 4
  8. 2023Differentiable Bayesian Structure Learning with Acyclicity Assurancecited by 3
  9. 2023Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approachcited by 2
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  11. 2026Causal Ensemble Agent: Hierarchical Causal Discovery with LLM-guided Expert Reweightingcited by 2
  12. 2025Goal-Oriented Sequential Bayesian Experimental Design for Causal Learningcited by 1
  13. 2022Pitfalls of Climate Network Construction: A Statistical Perspectivecited by 0
  14. 2024Exploring Biomarker Relationships in Both Type 1 and Type 2 Diabetes Mellitus Through a Bayesian Network Analysis Approachcited by 0
  15. 2025BaMANI: Bayesian Multi-Algorithm causal Network Inferencecited by 0
  16. 2026Stable Causal Discovery via Directed Acyclic Graph Aggregationcited by 0
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  18. 2026Joint Causal Structure and Cluster Discovery Using Variational Inferencecited by 0
  19. 2026ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMscited by 0