Daniel W. Apley

Affiliations:
  • Northwestern University, Evanston, IL, USA


According to our database1, Daniel W. Apley authored at least 41 papers between 1999 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Fully Bayesian Inference for Latent Variable Gaussian Process Models.
SIAM/ASA J. Uncertain. Quantification, December, 2023

Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors.
Technometrics, April, 2023

Interpretable Architecture Neural Networks for Function Visualization.
CoRR, 2023

2022
Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data.
Technometrics, 2022

Robust monitoring of stochastic textured surfaces.
Int. J. Prod. Res., 2022

Uncertainty-aware Mixed-variable Machine Learning for Materials Design.
CoRR, 2022

2021
Bias-corrected Estimation of the Density of a Conditional Expectation in Nested Simulation Problems.
ACM Trans. Model. Comput. Simul., 2021

Coefficient tree regression for generalized linear models.
Stat. Anal. Data Min., 2021

Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors.
CoRR, 2021

2020
A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors.
Technometrics, 2020

Technometrics 2019 Editor's Report.
Technometrics, 2020

Including a Nugget Effect in Lifted Brownian Covariance Models.
SIAM/ASA J. Uncertain. Quantification, 2020

2019
Technometrics 2018 Editor's Report.
Technometrics, 2019

Projection-free kernel principal component analysis for denoising.
Neurocomputing, 2019

An exploratory analysis approach for understanding variation in stochastic textured surfaces.
Comput. Stat. Data Anal., 2019

Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables.
CoRR, 2019

2018
Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis.
IEEE Trans. Neural Networks Learn. Syst., 2018

A Monitoring and Diagnostic Approach for Stochastic Textured Surfaces.
Technometrics, 2018

Patchwork Kriging for Large-scale Gaussian Process Regression.
J. Mach. Learn. Res., 2018

2017
Lifted Brownian Kriging Models.
Technometrics, 2017

Technometrics 2017 Editor's Report.
Technometrics, 2017

Batch Sample Design from Databases for Logistic Regression.
Qual. Reliab. Eng. Int., 2017

2016
Discovering the Nature of Variation in Nonlinear Profile Data.
Technometrics, 2016

A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records.
J. Am. Medical Informatics Assoc., 2016

2014
Feature selection for noisy variation patterns using kernel principal component analysis.
Knowl. Based Syst., 2014

2012
Tangent Hyperplane Kernel Principal Component Analysis for Denoising.
IEEE Trans. Neural Networks Learn. Syst., 2012

Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean.
Technometrics, 2012

A time-dependent proportional hazards survival model for credit risk analysis.
J. Oper. Res. Soc., 2012

2011
Improved design of robust exponentially weighted moving average control charts for autocorrelated processes.
Qual. Reliab. Eng. Int., 2011

Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation.
Oper. Res., 2011

Image denoising with a multi-phase kernel principal component approach and an ensemble version.
Proceedings of the 2011 IEEE Applied Imagery Pattern Recognition Workshop: Imaging for Decision Making, 2011

2010
Comment.
Technometrics, 2010

2008
Blind Identification of Manufacturing Variation Patterns by Combining Source Separation Criteria.
Technometrics, 2008

2006
Optimal Design of Second-Order Linear Filters for Control Charting.
Technometrics, 2006

2005
A characterization of diagnosability conditions for variance components analysis in assembly operations.
IEEE Trans Autom. Sci. Eng., 2005

2004
Cautious Control of Industrial Process Variability With Uncertain Input and Disturbance Model Parameters.
Technometrics, 2004

2003
Identifying Spatial Variation Patterns in Multivariate Manufacturing Processes - A Blind Separation Approach.
Technometrics, 2003

Design of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes With Model Uncertainty.
Technometrics, 2003

MLPCA Based Logistical Regression Analysis for Pattern Clustering in Manufacturing Processes.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2003

2001
A Factor-Analysis Method for Diagnosing Variability in Mulitvariate Manufacturing Processes.
Technometrics, 2001

1999
An order downdating algorithm for tracking system order and parameters in recursive least squares identification.
IEEE Trans. Signal Process., 1999


  Loading...