An efficient method for parametric yield optimization of MOS integrated circuits. - Tat-Kwan Yu; Sung-Mo Kang; Jerome Sacks; William J. Welch (ICCAD, 1989)

Parametric yield optimization of CMOS analogue circuits by quadratic statistical circuit performance models. - Tat-Kwan Yu; Sung-Mo Kang; Jerome Sacks; William J. Welch (Int. J. Circuit Theory Appl., 1991)

Integrated circuit design optimization using a sequential strategy. - Maria C. Bernardo; Robert J. Buck; Lihsin Liu; William A. Nazaret; Jerome Sacks; William J. Welch (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 1992)

Efficient Global Optimization of Expensive Black-Box Functions. - Donald R. Jones; Matthias Schonlau; William J. Welch (J. Glob. Optim., 1998)

Uniform Coverage Designs for Molecule Selection. - Raymond L. Lam; William J. Welch; S. Stanley Young (Technometrics, 2002)

Dynamic variable selection in SNP genotype autocalling from APEX microarray data. - Mohua Podder; William J. Welch; Ruben H. Zamar; Scott J. Tebbutt (BMC Bioinform., 2006)

Exploration of Cluster Structure-Activity Relationship Analysis in Efficient High-Throughput Screening. - X. Sunny Wang; G. A. Salloum; Hugh A. Chipman; William J. Welch; S. Stanley Young (J. Chem. Inf. Model., 2007)

Choosing the Sample Size of a Computer Experiment: A Practical Guide. - Jason L. Loeppky; Jerome Sacks; William J. Welch (Technometrics, 2009)

Automatic genotype calling of single nucleotide polymorphisms using a linear grouping algorithm. - Guohua Yan; William J. Welch; Ruben H. Zamar; Loubna Akhabir; Treena McDonald (ICNC, 2011)

ChemModLab: A Web-Based Cheminformatics Modeling Laboratory. - Jacqueline M. Hughes-Oliver; Atina D. Brooks; William J. Welch; Morteza G. Khaledi; Douglas M. Hawkins; S. Stanley Young; Kirtesh Patil; Gary W. Howell; Raymond T. Ng; Moody T. Chu (Silico Biol., 2012)

Harvesting Classification Trees for Drug Discovery. - Yan Yuan; Hugh A. Chipman; William J. Welch (J. Chem. Inf. Model., 2012)

Exploiting Multiple Descriptor Sets in QSAR Studies. - Jabed H. Tomal; William J. Welch; Ruben H. Zamar (J. Chem. Inf. Model., 2016)

Using a Gaussian Process as a Nonparametric Regression Model. - James R. Gattiker; Michael S. Hamada; David Higdon; Matthias Schonlau; William J. Welch (Qual. Reliab. Eng. Int., 2016)

Comment: Expected Improvement for Efficient Blackbox Constrained Optimization. - Hao Chen 104; William J. Welch (Technometrics, 2016)

Flexible Correlation Structure for Accurate Prediction and Uncertainty Quantification in Bayesian Gaussian Process Emulation of a Computer Model. - Hao Chen 104; Jason L. Loeppky; William J. Welch (SIAM/ASA J. Uncertain. Quantification, 2017)

Upward Mobility for Underrepresented Students: A Model for a Cohort-Based Bachelor's Degree in Computer Science. - Sathya Narayanan; Kathryn I. Cunningham; Sonia M. Arteaga; William J. Welch; Leslie Maxwell; Zechariah Chawinga; Bude Su (SIGCSE, 2018)

Bayesian Optimization Using Monotonicity Information and Its Application in Machine Learning Hyperparameter. - Wenyi Wang; William J. Welch (CoRR, 2018)

Upward mobility for underrepresented students: a model for a cohort-based bachelor's degree in computer science. - Sathya Narayanan; Kathryn Cunningham; Sonia M. Arteaga; William J. Welch; Leslie Maxwell; Zechariah Chawinga; Bude Su (Inroads, 2018)

Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images. - Michael Fernández; Fuqiang Ban; Godwin Woo; Michael Hsing; Takeshi Yamazaki; Eric Leblanc; Paul S. Rennie; William J. Welch; Artem Cherkasov (J. Chem. Inf. Model., 2018)

Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile. - Hao Chen 104; William J. Welch (CoRR, 2019)

Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space With Softplus Loss. - Xin Ding; Z. Jane Wang 001; William J. Welch (IEEE Trans. Signal Process., 2020)

Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images Based on Annotation-Free Training Samples. - Xin Ding; Qiong Zhang; William J. Welch (CICAI, 2021)

CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation. - Xin Ding; Yongwei Wang; Zuheng Xu; William J. Welch; Z. Jane Wang 001 (ICLR, 2021)

EPX: An R package for the ensemble of subsets of variables for highly unbalanced binary classification. - Grace G. Hsu; Jabed H. Tomal; William J. Welch (Comput. Biol. Medicine, 2021)

Efficient Subsampling for Generating High-Quality Images from Conditional Generative Adversarial Networks. - Xin Ding; Yongwei Wang; Z. Jane Wang 001; William J. Welch (CoRR, 2021)

Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code. - Sonja Isberg; William J. Welch (J. Comput. Graph. Stat., 2022)

Data-Adaptive Dimensional Analysis for Accurate Interpolation and Extrapolation in Computer Experiments. - G. Alexi Rodriguez-Arelis; William J. Welch (CoRR, 2023)

Efficient subsampling of realistic images from GANs conditional on a class or a continuous variable. - Xin Ding; Yongwei Wang; Z. Jane Wang 001; William J. Welch (Neurocomputing, 2023)

Distilling and transferring knowledge via cGAN-generated samples for image classification and regression. - Xin Ding; Yongwei Wang; Zuheng Xu; Z. Jane Wang 001; William J. Welch (Expert Syst. Appl., 2023)

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms. - Xin Ding; Yongwei Wang; Zuheng Xu; William J. Welch; Z. Jane Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)