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Beyond point estimation: explaining the posterior in Bayesian cluster analysis
The Bayesian approach to clustering is often appreciated for its ability to provide uncertainty in the partition structure. However, summarising the posterior distribution over partitions remains challenging, due to its discrete, unordered and extremely high-dimensional nature. Existing approaches t
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