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Motivated by a computer experiment for the design of a rocket booster, this paper explores nonstationary modeling methodologies that couple stationary Gaussian processes with treed partitioning.â€¦ (More)

- Herbert K. H. Lee, David M. Higdon, Zhuoxin Bi, Marco A. R. Ferreira, Mike West
- Technometrics
- 2002

We give an approach for using flow information from a system of wells to characterize hydrologic properties of an aquifer. In particular, we consider experiments where an impulse of tracer fluid isâ€¦ (More)

This paper explores nonparametric and semiparametric nonstationary modeling methodologies that couple stationary Gaussian processes and (limiting) linear models with treed partitioning. Partitioningâ€¦ (More)

- Robert B. Gramacy, Herbert K. H. Lee
- Technometrics
- 2009

Computer experiments are often performed to allow modeling of a response surface of a physical experiment that can be too costly or difficult to run except using a simulator. Running the experimentâ€¦ (More)

Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are unnecessary inâ€¦ (More)

- Herbert K. H. Lee
- Neural Networks
- 2000

In this paper we show that the posterior distribution for feedforward neural networks is asymptotically consistent. This paper extends earlier results on universal approximation properties of neuralâ€¦ (More)

Optimization of complex functions, such as the output of computer simulators, is a difficult task that has received much attention in the literature. A less studied problem is that of optimizationâ€¦ (More)

- Dave Higdon, Herbert K. H. Lee, Zhuoxin Bi
- IEEE Trans. Signal Processing
- 2002

The Bayesian approach allows one to easily quantify uncertainty, at least in theory. In practice, however, MCMC can be computationally expensive, particularly in complicated inverse problems. Here weâ€¦ (More)

- Robert B. Gramacy, Herbert K. H. Lee
- Computational Statistics & Data Analysis
- 2008

Gaussian processes retain the linear model either as a special case, or in the limit. We show how this relationship can be exploited when the data are at least partially linear. However from theâ€¦ (More)

- Herbert K. H. Lee
- J. Classification
- 2001

Classification rates on out-of-sample predictions can often be improved through the use of model selection when fitting a model on the training data. Using correlated predictors or fitting a model ofâ€¦ (More)