Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference
arXiv 2606.07677•13e45742ca163c29bd2e7a191f74e6d23a4f66b475abd7f82362188de2397851
CATEbarycentric-projectionbayesian-hypergraphbayesian-inferencebayesian-optimization-diffusion-modelscausal-discoverycausal-forestcyclic-interactionselectronic-health-recordsfMRIfinite-mixtureshidden-variableshypergraph-modelsinverse-probability-weightinglocation-scale-noisemarginal-independencemulti-disease-modelingoptimal-transportproximal-policy-optimizationreinforcement-learningriemannian-manifoldsstein-variational-gradient-descentsurvival-analysistransfer-learningvariational-inference
Paper metadata
- arXiv ID
- 2606.07677
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- 13e45742ca163c29bd2e7a191f74e6d23a4f66b475abd7f82362188de2397851
- Enrichment time
- 2026-06-09T07:23:57Z
- AI-assisted enrichment
- Yes
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