H. Chipman

Publications80
h-index23
Citations4,773
Highly Influential Citations676
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BART: Bayesian Additive Regression Trees
We develop a Bayesian "sum-of-trees" model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative Bayesian… Expand
  • 927
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Bayesian CART Model Search
Abstract In this article we put forward a Bayesian approach for finding classification and regression tree (CART) models. The two basic components of this approach consist of prior specification and… Expand
  • 612
  • 127
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Bayes and big data: the consensus Monte Carlo algorithm
TLDR
A useful definition of ‘big data’ is data that is too big to process comfortably on a single machine, either because of processor, memory, or disk bottlenecks. Expand
  • 297
  • 52
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Bayesian variable selection with related predictors
  • H. Chipman
  • Computer Science, Mathematics
  • 30 October 1995
TLDR
This paper develops mathematical representations of this and other relations between predictors, which may then be incorporated in a model selection procedure. Expand
  • 331
  • 47
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The Practical Implementation of Bayesian Model Selection
TLDR
In principle, the Bayesian approach to model selection is straightforward. Expand
  • 427
  • 45
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Adaptive Bayesian Wavelet Shrinkage
Abstract When fitting wavelet based models, shrinkage of the empirical wavelet coefficients is an effective tool for denoising the data. This article outlines a Bayesian approach to shrinkage,… Expand
  • 592
  • 30
  • PDF
A Bayesian variable-selection approach for analyzing designed experiments with complex aliasing
Experiments using designs with complex aliasing patterns are often performed—for example, twolevel nongeometric Plackett-Burman designs, multilevel and mixed-level fractional factorial designs,… Expand
  • 243
  • 28
  • PDF
Interpretable dimension reduction
Abstract The analysis of high-dimensional data often begins with the identification of lower dimensional subspaces. Principal component analysis is a dimension reduction technique that identifies… Expand
  • 48
  • 13
  • PDF
Bayesian Treed Models
TLDR
We propose a Bayesian approach for finding and fitting parametric treed models, in particular focusing on Bayesian treed regression. Expand
  • 179
  • 12
  • PDF
Bayesian Ensemble Learning
TLDR
We develop a Bayesian "sum-of-trees" model, named BART, where each tree is constrained by a prior to be a weak learner. Expand
  • 71
  • 11
  • PDF