Daniel W. Apley

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 31

Top Topics

Kernel Principal Component Analysis

Gaussian Process

Textured Surfaces

Generalized Linear Models

Top Venues

SIAM/ASA J. Uncertain. Quantification

Publications

Özge Sürer, Daniel W. Apley, Edward C. Malthouse
Coefficient tree regression: fast, accurate and interpretable predictive modeling. Mach. Learn. 113 (7) (2024)
Wei Liu, Satyajit Mojumder, Wing Kam Liu, Wei Chen, Daniel W. Apley
Simulation-Free Determination of Microstructure Representative Volume Element Size via Fisher Scores. CoRR (2024)
Shengtong Zhang, Daniel W. Apley
Interpretable Architecture Neural Networks for Function Visualization. J. Comput. Graph. Stat. 32 (4) (2023)
Shengtong Zhang, Daniel W. Apley
Interpretable Architecture Neural Networks for Function Visualization. CoRR (2023)
Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley
Fully Bayesian Inference for Latent Variable Gaussian Process Models. SIAM/ASA J. Uncertain. Quantification 11 (4) (2023)
Kungang Zhang, Anh Tuan Bui, Daniel W. Apley
Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors. Technometrics 65 (2) (2023)
Hengrui Zhang, Wei Wayne Chen, Akshay Iyer, Daniel W. Apley, Wei Chen
Uncertainty-aware Mixed-variable Machine Learning for Materials Design. CoRR (2022)
Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley
Fully Bayesian inference for latent variable Gaussian process models. CoRR (2022)
Anh Tuan Bui, Daniel W. Apley
Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data. Technometrics 64 (4) (2022)
Anh Tuan Bui, Daniel W. Apley
Robust monitoring of stochastic textured surfaces. Int. J. Prod. Res. 60 (16) (2022)
Ran Yang, David Kent, Daniel W. Apley, Jeremy Staum, David Ruppert
Bias-corrected Estimation of the Density of a Conditional Expectation in Nested Simulation Problems. ACM Trans. Model. Comput. Simul. 31 (4) (2021)
Liwei Wang, Suraj Yerramilli, Akshay Iyer, Daniel W. Apley, Ping Zhu, Wei Chen
Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors. CoRR (2021)
Özge Sürer, Daniel W. Apley, Edward C. Malthouse
Coefficient tree regression for generalized linear models. Stat. Anal. Data Min. 14 (5) (2021)
Yichi Zhang, Siyu Tao, Wei Chen, Daniel W. Apley
A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors. Technometrics 62 (3) (2020)
Kungang Zhang, Anh Tuan Bui, Daniel W. Apley
Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors. CoRR (2020)
Yang Yu, Ning Zhang, Daniel W. Apley, Wenxin Jiang
Including a Nugget Effect in Lifted Brownian Covariance Models. SIAM/ASA J. Uncertain. Quantification 8 (4) (2020)
Daniel W. Apley
Technometrics 2019 Editor's Report. Technometrics 62 (1) (2020)
Anh Tuan Bui, Daniel W. Apley
An exploratory analysis approach for understanding variation in stochastic textured surfaces. Comput. Stat. Data Anal. 137 (2019)
Yichi Zhang, Daniel W. Apley, Wei Chen
Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables. CoRR (2019)
Daniel W. Apley
Technometrics 2018 Editor's Report. Technometrics 61 (1) (2019)
Anh Tuan Bui, Joon-Ku Im, Daniel W. Apley, George C. Runger
Projection-free kernel principal component analysis for denoising. Neurocomputing 357 (2019)
Phillip Howard, Daniel W. Apley, George Runger
Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis. IEEE Trans. Neural Networks Learn. Syst. 29 (1) (2018)
Anh Tuan Bui, Daniel W. Apley
A Monitoring and Diagnostic Approach for Stochastic Textured Surfaces. Technometrics 60 (1) (2018)
Yichi Zhang, Siyu Tao, Wei Chen, Daniel W. Apley
A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors. CoRR (2018)
Chiwoo Park, Daniel W. Apley
Patchwork Kriging for Large-scale Gaussian Process Regression. J. Mach. Learn. Res. 19 (2018)
Daniel W. Apley
Technometrics 2017 Editor's Report. Technometrics 59 (4) (2017)
Chiwoo Park, Daniel W. Apley
Patchwork Kriging for Large-scale Gaussian Process Regression. CoRR (2017)
Matthew Plumlee, Daniel W. Apley
Lifted Brownian Kriging Models. Technometrics 59 (2) (2017)
Liwen Ouyang, Daniel W. Apley, Sanjay Mehrotra
Batch Sample Design from Databases for Logistic Regression. Qual. Reliab. Eng. Int. 33 (1) (2017)
Liwen Ouyang, Daniel W. Apley, Sanjay Mehrotra
A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records. J. Am. Medical Informatics Assoc. 23 (e1) (2016)
Zhenyu Shi, Daniel W. Apley, George C. Runger
Discovering the Nature of Variation in Nonlinear Profile Data. Technometrics 58 (3) (2016)
Anshuman Sahu, Daniel W. Apley, George C. Runger
Feature selection for noisy variation patterns using kernel principal component analysis. Knowl. Based Syst. 72 (2014)
Daniel W. Apley
Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean. Technometrics 54 (3) (2012)
Joon-Ku Im, Daniel W. Apley, C. Qi, X. Shan
A time-dependent proportional hazards survival model for credit risk analysis. J. Oper. Res. Soc. 63 (3) (2012)
Joon-Ku Im, Daniel W. Apley, George C. Runger
Tangent Hyperplane Kernel Principal Component Analysis for Denoising. IEEE Trans. Neural Networks Learn. Syst. 23 (4) (2012)
Yunpeng Sun, Daniel W. Apley, Jeremy Staum
Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation. Oper. Res. 59 (4) (2011)
Anshuman Sahu, George C. Runger, Daniel W. Apley
Image denoising with a multi-phase kernel principal component approach and an ensemble version. AIPR (2011)
Hyun Cheol Lee, Daniel W. Apley
Improved design of robust exponentially weighted moving average control charts for autocorrelated processes. Qual. Reliab. Eng. Int. 27 (3) (2011)
Daniel W. Apley
Comment. Technometrics 52 (3) (2010)
Xuemei Shan, Daniel W. Apley
Blind Identification of Manufacturing Variation Patterns by Combining Source Separation Criteria. Technometrics 50 (3) (2008)
Chang-Ho Chin, Daniel W. Apley
Optimal Design of Second-Order Linear Filters for Control Charting. Technometrics 48 (3) (2006)
Daniel W. Apley, Yu Ding
A characterization of diagnosability conditions for variance components analysis in assembly operations. IEEE Trans Autom. Sci. Eng. 2 (2) (2005)
Daniel W. Apley, Jeong-Bae Kim
Cautious Control of Industrial Process Variability With Uncertain Input and Disturbance Model Parameters. Technometrics 46 (2) (2004)
Feng Zhang, Daniel W. Apley
MLPCA Based Logistical Regression Analysis for Pattern Clustering in Manufacturing Processes. IDEAL (2003)
Daniel W. Apley, Ho-Young Lee
Identifying Spatial Variation Patterns in Multivariate Manufacturing Processes - A Blind Separation Approach. Technometrics 45 (3) (2003)
Daniel W. Apley, Hyun Cheol Lee
Design of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes With Model Uncertainty. Technometrics 45 (3) (2003)
Daniel W. Apley, Jianjun Shi
A Factor-Analysis Method for Diagnosing Variability in Mulitvariate Manufacturing Processes. Technometrics 43 (1) (2001)
Daniel W. Apley, Jianjun Shi
An order downdating algorithm for tracking system order and parameters in recursive least squares identification. IEEE Trans. Signal Process. 47 (11) (1999)