mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models. - Luca Scrucca; Michael Fop; Thomas Brendan Murphy; Adrian E. Raftery (R J., 2016)

Model-based clustering with sparse covariance matrices. - Michael Fop; Thomas Brendan Murphy; Luca Scrucca (Stat. Comput., 2019)

A stochastic block model for interaction lengths. - Riccardo Rastelli; Michael Fop (Adv. Data Anal. Classif., 2020)

Unobserved classes and extra variables in high-dimensional discriminant analysis. - Michael Fop; Pierre-Alexandre Mattei; Charles Bouveyron; Thomas Brendan Murphy (Adv. Data Anal. Classif., 2022)

Group-Wise Shrinkage Estimation in Penalized Model-Based Clustering. - Alessandro Casa; Andrea Cappozzo; Michael Fop (J. Classif., 2022)

A Dirichlet stochastic block model for composition-weighted networks. - Iuliia Promskaia; Adrian O'Hagan; Michael Fop (Comput. Stat. Data Anal., 2025)

A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral images. - Ganesh Babu; Aoife Gowen; Michael Fop; Isobel Claire Gormley (Adv. Data Anal. Classif., 2025)