most citedKernel learning approaches for summarising and combining posterior similarity matrices

2 citations · 4 across the 2 of their papers we have counts for

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stat.ME2020★ 2 cited

Kernel learning approaches for summarising and combining posterior similarity matrices

Alessandra Cabassi, Sylvia Richardson, Paul D. W. Kirk

When using Markov chain Monte Carlo (MCMC) algorithms to perform inference for Bayesian clustering models, such as mixture models, the output is typically a sample of clusterings (…

stat.ME2020★ 2 cited

Two-step penalised logistic regression for multi-omic data with an application to cardiometabolic syndrome

Alessandra Cabassi, Denis Seyres, Mattia Frontini +1

Building classification models that predict a binary class label on the basis of high dimensional multi-omics datasets poses several challenges, due to the typically widely differi…