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Found 2 papers, 2 papers with code
Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes
Next, the partial separability structure is shown to be particularly useful in order to provide a well-defined functional Gaussian graphical model that can be identified with a sequence of finite-dimensional graphical models, each of identical fixed dimension.
Distributionally Robust Formulation and Model Selection for the Graphical Lasso
As a consequence of this formulation, the radius of the Wasserstein ambiguity set is directly related to the regularization parameter in the estimation problem.
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