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Found 2 papers, 2 papers with code
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging
Several problems in neuroimaging and beyond require inference on the parameters of multi-task sparse hierarchical regression models.
Joint Learning of Full-structure Noise in Hierarchical Bayesian Regression Models
We consider hierarchical Bayesian (type-II maximum likelihood) regression models for observations with latent variables for source and noise, where parameters of priors for source and noise terms need to be estimated jointly from data.
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