Research map / Probabilistic and scientific modeling / Causal discovery
Bayesian Structure Learning by Recursive Bootstrap
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Child | predictive log probability: -68861 ($\pm$110) -> -65671 ($\pm$79) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Insurance | predictive log probability: -71296 ($\pm$115) -> -70634 ($\pm$99) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Mildew | predictive log probability: -288677 ($\pm$1323) -> -279686 ($\pm$1028) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Alarm | predictive log probability: -52198 ($\pm$117) -> -51173.5 ($\pm$127) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Barley | predictive log probability: -340317 ($\pm$389) -> -339057 ($\pm$804) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Hailfinder | predictive log probability: -291632.5 ($\pm$259) -> -289074 ($\pm$120) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Munin | predictive log probability: -447481 ($\pm$1148) -> -436309 ($\pm$593) | Helped |
| Use recursive bootstrap with B-RAI MAP instead of RAI | Bayesian network structure learning · Link | predictive log probability: -1857751 ($\pm$887) -> -1772132 ($\pm$659) | Helped |
| Use recursive rather than classic non-parametric bootstrap over RAI | B-RAI · Alarm | number of CI-tests | Helped |
| Use B-RAI for top-scoring structural-feature estimates rather than the optimal k-best baseline | Model averaging · Asia, Cancer, Earthquake, Survey | area under ROC curve | No clear effect |
Closest papers by meaning
- Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias (NeurIPS 2021 · similarity 0.89)
- Extendable and Iterative Structure Learning Strategy for Bayesian Networks (ICLR 2025 · similarity 0.88)
- Learning Bayesian Networks in the Presence of Structural Side Information (AAAI 2022 · similarity 0.87)
- DiBS: Differentiable Bayesian Structure Learning (NeurIPS 2021 · similarity 0.87)
- Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss (NeurIPS 2024 · similarity 0.86)
- Distribution Learning Meets Graph Structure Sampling (NeurIPS 2025 · similarity 0.85)
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