Search Results for author: Daniel W. Apley

Found 8 papers, 4 papers with code

Interpretable Architecture Neural Networks for Function Visualization

no code implementations3 Mar 2023 Shengtong Zhang, Daniel W. Apley

Existing visualization tools do not allow one to visualize the effects of all the input variables simultaneously.

Fully Bayesian inference for latent variable Gaussian process models

1 code implementation4 Nov 2022 Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley

However, this plug-in approach will not account for uncertainty in estimation of the LVs, which can be significant especially with limited training data.

Bayesian Inference Gaussian Processes +1

Uncertainty-Aware Mixed-Variable Machine Learning for Materials Design

no code implementations11 Jul 2022 Hengrui Zhang, Wei Wayne Chen, Akshay Iyer, Daniel W. Apley, Wei Chen

Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods.

Bayesian Optimization BIG-bench Machine Learning +1

Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models

2 code implementations27 Dec 2016 Daniel W. Apley

When fitting black box supervised learning models (e. g., complex trees, neural networks, boosted trees, random forests, nearest neighbors, local kernel-weighted methods, etc.

Methodology

Local Gaussian process approximation for large computer experiments

no code implementations2 Mar 2013 Robert B. Gramacy, Daniel W. Apley

We provide a new approach to approximate emulation of large computer experiments.

Methodology Computation

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