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Found 4 papers, 2 papers with code
Bayesian inference in high-dimensional models
Bayesian methods have been proposed for such problems more recently, where the prior takes care of the sparsity structure.
Bayesian Inference
Statistics Theory
Statistics Theory
Bayesian Semi-supervised learning under nonparanormality
Semi-supervised learning is a classification method which makes use of both labeled data and unlabeled data for training.
Bayesian method for causal inference in spatially-correlated multivariate time series
A novel Bayesian method is proposed to detect weaker impacts and a multivariate structural time series model is used to capture the spatial correlation between stores through placing a $\mathcal{G}$-Wishart prior on the precision matrix.
Methodology
Multivariate Gaussian Network Structure Learning
We consider a graphical model where a multivariate normal vector is associated with each node of the underlying graph and estimate the graphical structure.
