A Novel Approach for Summarizing Posterior Inference in Bayesian Nonparametric Mixture Models Using Sliced Optimal Transport Metrics
This paper proposes a novel, model-agnostic method for summarizing posterior inference in Bayesian nonparametric mixture models, prioritizing density estimation of the mixing measure using sliced optimal transport distances.