Picture for Daniel W. Apley

Daniel W. Apley

Interpretable Architecture Neural Networks for Function Visualization

Add code
Mar 03, 2023
Viaarxiv icon

Fully Bayesian inference for latent variable Gaussian process models

Add code
Nov 04, 2022
Viaarxiv icon

Uncertainty-aware Mixed-variable Machine Learning for Materials Design

Add code
Jul 11, 2022
Figure 1 for Uncertainty-aware Mixed-variable Machine Learning for Materials Design
Figure 2 for Uncertainty-aware Mixed-variable Machine Learning for Materials Design
Figure 3 for Uncertainty-aware Mixed-variable Machine Learning for Materials Design
Figure 4 for Uncertainty-aware Mixed-variable Machine Learning for Materials Design
Viaarxiv icon

Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors

Add code
Dec 12, 2020
Figure 1 for Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors
Figure 2 for Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors
Figure 3 for Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors
Figure 4 for Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors
Viaarxiv icon

A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors

Add code
Jun 19, 2018
Figure 1 for A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors
Figure 2 for A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors
Figure 3 for A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors
Figure 4 for A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors
Viaarxiv icon