1.6k citations · 1.7k across the 16 of their papers we have counts for
16 papers
MLCBART: Multilabel Classification with Bayesian Additive Regression Trees
Jiahao Tian, Hugh Chipman, Thomas Loughin
Multilabel Classification (MLC) deals with the simultaneous classification of multiple binary labels. The task is challenging because, not only may there be arbitrarily different a…
Let's practice what we preach: Planning and interpreting simulation studies with design and analysis of experiments
Hugh Chipman, Derek Bingham
Statisticians recommend the Design and Analysis of Experiments (DAE) for evidence-based research but often use tables to present their own simulation studies. Could DAE do better?…
Heteroscedastic BART Using Multiplicative Regression Trees
Matthew Pratola, Hugh Chipman, Edward George +1
BART (Bayesian Additive Regression Trees) has become increasingly popular as a flexible and scalable nonparametric regression approach for modern applied statistics problems. For t…
mBART: Multidimensional Monotone BART
Hugh A. Chipman, Edward I. George, Robert E. McCulloch +1
For the discovery of regression relationships between Y and a large set of p potential predictors x 1 , . . . , x p , the flexible nonparametric nature of BART (Bayesian Additive R…
A Continuous-time Stochastic Block Model for Basketball Networks
Lu Xin, Mu Zhu, Hugh Chipman
For professional basketball, finding valuable and suitable players is the key to building a winning team. To deal with such challenges, basketball managers, scouts and coaches are…
Parallel Bayesian Additive Regression Trees
Matthew T. Pratola, Hugh A. Chipman, James R. Gattiker +3
Bayesian Additive Regression Trees (BART) is a Bayesian approach to flexible non-linear regression which has been shown to be competitive with the best modern predictive methods su…