Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Alexander Franks, Sang-Yun Oh, , | Summary: Gaussian Graphical models (GGM) are widely used to estimate the network structures in many applications ranging from biology to finance. In practice, data is often corrupted by latent confounders which biases inference of the underlying true graphical structure. […]
Continue.. Learning Gaussian Graphical Models with Latent Confounders