69 citations · 261 across the 20 of their papers we have counts for
6 papers · 1 filter
Dynamic Sparse Factor Analysis
Kenichiro McAlinn, Veronika Rockova, Enakshi Saha
Its conceptual appeal and effectiveness has made latent factor modeling an indispensable tool for multivariate analysis. Despite its popularity across many fields, there are outsta…
On Theory for BART
Veronika Rockova, Enakshi Saha
Ensemble learning is a statistical paradigm built on the premise that many weak learners can perform exceptionally well when deployed collectively. The BART method of Chipman et al…
The Median Probability Model and Correlated Variables
Marilena Barbieri, James O. Berger, Edward I. George +1
The median probability model (MPM) Barbieri and Berger (2004) is defined as the model consisting of those variables whose marginal posterior probability of inclusion is at least 0.…
Variable Selection with ABC Bayesian Forests
Yi Liu, Veronika Ročková, Yuexi Wang
Few problems in statistics are as perplexing as variable selection in the presence of very many redundant covariates. The variable selection problem is most familiar in parametric…
Posterior Concentration for Sparse Deep Learning
Nicholas Polson, Veronika Rockova
Spike-and-Slab Deep Learning (SS-DL) is a fully Bayesian alternative to Dropout for improving generalizability of deep ReLU networks. This new type of regularization enables provab…
Variance prior forms for high-dimensional Bayesian variable selection
Gemma E. Moran, Veronika Rockova, Edward I. George
Consider the problem of high dimensional variable selection for the Gaussian linear model when the unknown error variance is also of interest. In this paper, we show that the use o…