Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular ...

A five-minute formula from Alexander Denev that takes you through a simple probabilistic graphical model and explains how and why these are used. Find out more about the ground-breaking book, ...

Jian Guo, Elizaveta Levina, George Michailidis, Ji Zhu, Graphical Models for Ordinal Data, Journal of Computational and Graphical Statistics, Vol. 24, No. 1 (MARCH 2015), pp. 183-204 ...

Ming Yuan, Yi Lin, Model Selection and Estimation in the Gaussian Graphical Model, Biometrika, Vol. 94, No. 1 (Mar., 2007), pp. 19-35 Free online reading for over 10 million articles Save and organize ...

Topics include directed and undirected graphical models, exact and approximate inference methods, and supervised and unsupervised parameter and structure learning. Grades: Homework will involve both ...

In a paper published in National Science Review, the team of Pro. Liu present an innovative computational framework, the sample-perturbed Gaussian graphical model (sPGGM), designed to analyse ...

sPGGM: a sample-perturbed Gaussian graphical model for identifying pre-disease stages and signaling molecules of disease progression. Science China Press. Journal National Science Review DOI ...