Picture for Robert B. Gramacy

Robert B. Gramacy

Voronoi Candidates for Bayesian Optimization

Add code
Feb 07, 2024
Figure 1 for Voronoi Candidates for Bayesian Optimization
Figure 2 for Voronoi Candidates for Bayesian Optimization
Figure 3 for Voronoi Candidates for Bayesian Optimization
Figure 4 for Voronoi Candidates for Bayesian Optimization
Viaarxiv icon

Robust expected improvement for Bayesian optimization

Add code
Feb 16, 2023
Viaarxiv icon

Triangulation candidates for Bayesian optimization

Add code
Dec 14, 2021
Figure 1 for Triangulation candidates for Bayesian optimization
Figure 2 for Triangulation candidates for Bayesian optimization
Figure 3 for Triangulation candidates for Bayesian optimization
Figure 4 for Triangulation candidates for Bayesian optimization
Viaarxiv icon

Entropy-based adaptive design for contour finding and estimating reliability

Add code
May 24, 2021
Figure 1 for Entropy-based adaptive design for contour finding and estimating reliability
Viaarxiv icon

Sensitivity Prewarping for Local Surrogate Modeling

Add code
Jan 15, 2021
Figure 1 for Sensitivity Prewarping for Local Surrogate Modeling
Figure 2 for Sensitivity Prewarping for Local Surrogate Modeling
Figure 3 for Sensitivity Prewarping for Local Surrogate Modeling
Figure 4 for Sensitivity Prewarping for Local Surrogate Modeling
Viaarxiv icon

Active Learning for Deep Gaussian Process Surrogates

Add code
Dec 15, 2020
Figure 1 for Active Learning for Deep Gaussian Process Surrogates
Figure 2 for Active Learning for Deep Gaussian Process Surrogates
Figure 3 for Active Learning for Deep Gaussian Process Surrogates
Figure 4 for Active Learning for Deep Gaussian Process Surrogates
Viaarxiv icon

Locally induced Gaussian processes for large-scale simulation experiments

Add code
Aug 28, 2020
Figure 1 for Locally induced Gaussian processes for large-scale simulation experiments
Figure 2 for Locally induced Gaussian processes for large-scale simulation experiments
Figure 3 for Locally induced Gaussian processes for large-scale simulation experiments
Figure 4 for Locally induced Gaussian processes for large-scale simulation experiments
Viaarxiv icon

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian

Add code
May 31, 2016
Figure 1 for Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian
Figure 2 for Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian
Figure 3 for Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian
Figure 4 for Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian
Viaarxiv icon

Gaussian Process Structural Equation Models with Latent Variables

Add code
Aug 09, 2014
Figure 1 for Gaussian Process Structural Equation Models with Latent Variables
Figure 2 for Gaussian Process Structural Equation Models with Latent Variables
Figure 3 for Gaussian Process Structural Equation Models with Latent Variables
Figure 4 for Gaussian Process Structural Equation Models with Latent Variables
Viaarxiv icon

Sequential Design for Optimal Stopping Problems

Add code
Jul 29, 2014
Figure 1 for Sequential Design for Optimal Stopping Problems
Figure 2 for Sequential Design for Optimal Stopping Problems
Figure 3 for Sequential Design for Optimal Stopping Problems
Figure 4 for Sequential Design for Optimal Stopping Problems
Viaarxiv icon