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scalable-bayesian-models

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BayesCOOP is a scalable Bayesian framework for supervised multimodal data integration. It combines the Bayesian bootstrap with a jittered group spike-and-slab Laplace prior to enable cooperative learning across heterogeneous data modalities, with principled uncertainty quantification.

  • Updated Nov 25, 2025
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