Mixture of Conditional Gaussian Graphical Models for unlabelled heterogeneous populations in the presence of co-factors
Conditional correlation networks, within Gaussian Graphical Models (GGM), are widely used
to describe the direct interactions between the components of a random vector. In the case …
to describe the direct interactions between the components of a random vector. In the case …
Mixtures of Gaussian Graphical Models with Constraints
T Lartigue - 2020 - theses.hal.science
Describing the co-variations between several observed random variables is a delicate
problem. Dependency networks are popular tools that depict the relations between variables …
problem. Dependency networks are popular tools that depict the relations between variables …
Importance-penalized joint graphical lasso (IPJGL): Differential network inference via GGMs
Motivation Differential network inference is a fundamental and challenging problem to reveal
gene interactions and regulation relationships under different conditions. Many algorithms …
gene interactions and regulation relationships under different conditions. Many algorithms …