14 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
Ideal Bayesian Spatial Adaptation
Veronika Rockova, Judith Rousseau
Many real-life applications involve estimation of curves that exhibit complicated shapes including jumps or varying-frequency oscillations. Practical methods have been devised that…
Uncertainty Quantification for Sparse Deep Learning
Yuexi Wang, Veronika Ročková
Deep learning methods continue to have a decided impact on machine learning, both in theory and in practice. Statistical theoretical developments have been mostly concerned with ap…
On Semi-parametric Bernstein-von Mises Theorems for BART
Veronika Rockova
Few methods in Bayesian non-parametric statistics/ machine learning have received as much attention as Bayesian Additive Regression Trees (BART). While BART is now routinely perfor…
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.…
Bayesian Dyadic Trees and Histograms for Regression
Stephanie van der Pas, Veronika Rockova
Many machine learning tools for regression are based on recursive partitioning of the covariate space into smaller regions, where the regression function can be estimated locally.…