113 citations · 294 across the 25 of their papers we have counts for
3 papers · 1 filter
Robust, Accurate Stochastic Optimization for Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen +3
We consider the problem of fitting variational posterior approximations using stochastic optimization methods. The performance of these approximations depends on (1) how well the v…
Independent finite approximations for Bayesian nonparametric inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero +2
Completely random measures (CRMs) and their normalizations (NCRMs) offer flexible models in Bayesian nonparametrics. But their infinite dimensionality presents challenges for infer…
Reproducible Model Selection Using Bagged Posteriors
Jonathan H. Huggins, Jeffrey W. Miller
Bayesian model selection is premised on the assumption that the data are generated from one of the postulated models. However, in many applications, all of these models are incorre…