7 citations · 13 across the 3 of their papers we have counts for
3 papers
Fast robustness quantification with variational Bayes
Ryan Giordano, Tamara Broderick, Rachael Meager +2
Bayesian hierarchical models are increasing popular in economics. When using hierarchical models, it is useful not only to calculate posterior expectations, but also to measure the…
Risk and Regret of Hierarchical Bayesian Learners
Jonathan H. Huggins, Joshua B. Tenenbaum
Common statistical practice has shown that the full power of Bayesian methods is not realized until hierarchical priors are used, as these allow for greater "robustness" and the ab…
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi +1
Markov jump processes (MJPs) are used to model a wide range of phenomena from disease progression to RNA path folding. However, maximum likelihood estimation of parametric models l…