Search Results for author:
Found 3 papers, 0 papers with code
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models
We use a latent tree graphical model to analyze gene expression without relying on transcription factor expression as a proxy for regulator activity.
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs
We consider a challenging instance of this problem when some of the nodes are latent or hidden.
Learning loopy graphical models with latent variables: Efficient methods and guarantees
The problem of structure estimation in graphical models with latent variables is considered.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
