3 papers
stat.ME2025
A discomfort-informed adaptive Gibbs sampler for finite mixture models
Davide Fabbrico, Andi Q. Wang, Sebastiano Grazzi +5
Finite mixture models are frequently used to uncover latent structures in high-dimensional datasets (e.g.\ identifying clusters of patients in electronic health records). The infer…
stat.ML2025
Federated Variational Inference for Bayesian Mixture Models
Jackie Rao, Francesca L. Crowe, Tom Marshall +2
We present a federated learning approach for Bayesian model-based clustering of large-scale binary and categorical datasets. We introduce a principled 'divide and conquer' inferenc…
stat.CO2024
Annealed variational mixtures for disease subtyping and biomarker discovery
Emma Prevot, Rory Toogood, Filippo Pagani +1
Cluster analyses of high-dimensional data are often hampered by the presence of large numbers of variables that do not provide relevant information, as well as the perennial issue…