William J. Welch

According to our database, William J. Welch authored at least 29 papers between 1989 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Distilling and transferring knowledge via cGAN-generated samples for image classification and regression.

Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch

Expert Syst. Appl., March, 2023

Efficient subsampling of realistic images from GANs conditional on a class or a continuous variable.

Xin Ding, Yongwei Wang, Z. Jane Wang, William J. Welch

Neurocomputing, 2023

Data-Adaptive Dimensional Analysis for Accurate Interpolation and Extrapolation in Computer Experiments.

G. Alexi Rodriguez-Arelis, William J. Welch

CoRR, 2023

2022

Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code.

Sonja Isberg, William J. Welch

J. Comput. Graph. Stat., October, 2022

2021

Efficient Subsampling for Generating High-Quality Images from Conditional Generative Adversarial Networks.

Xin Ding, Yongwei Wang, Z. Jane Wang, William J. Welch

CoRR, 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

CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation.

Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang

Proceedings of the 9th International Conference on Learning Representations, 2021

Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images Based on Annotation-Free Training Samples.

Xin Ding, Qiong Zhang, William J. Welch

Proceedings of the Artificial Intelligence - First CAAI International Conference, 2021

2020

Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space With Softplus Loss.

Xin Ding, Z. Jane Wang, William J. Welch

IEEE Trans. Signal Process., 2020

2019

Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile.

Hao Chen, William J. Welch

CoRR, 2019

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

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

Bayesian Optimization Using Monotonicity Information and Its Application in Machine Learning Hyperparameter.

Wenyi Wang, William J. Welch

CoRR, 2018

2017

Flexible Correlation Structure for Accurate Prediction and Uncertainty Quantification in Bayesian Gaussian Process Emulation of a Computer Model.

Hao Chen, Jason L. Loeppky, William J. Welch

SIAM/ASA J. Uncertain. Quantification, 2017

2016

Comment: Expected Improvement for Efficient Blackbox Constrained Optimization.

Hao Chen, William J. Welch

Technometrics, 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

Exploiting Multiple Descriptor Sets in QSAR Studies.

Jabed H. Tomal, William J. Welch, Ruben H. Zamar

J. Chem. Inf. Model., 2016

2012

Harvesting Classification Trees for Drug Discovery.

Yan Yuan, Hugh A. Chipman, William J. Welch

J. Chem. Inf. Model., 2012

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

2011

Automatic genotype calling of single nucleotide polymorphisms using a linear grouping algorithm.

Guohua Yan, William J. Welch, Ruben H. Zamar, Loubna Akhabir, Treena McDonald

Proceedings of the Seventh International Conference on Natural Computation, 2011

2009

Choosing the Sample Size of a Computer Experiment: A Practical Guide.

Jason L. Loeppky, Jerome Sacks, William J. Welch

Technometrics, 2009

2007

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

2006

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

2002

Uniform Coverage Designs for Molecule Selection.

Raymond L. Lam, William J. Welch, S. Stanley Young

Technometrics, 2002

1998

Efficient Global Optimization of Expensive Black-Box Functions.

Donald R. Jones, Matthias Schonlau, William J. Welch

J. Glob. Optim., 1998

1992

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

1991

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

1989

An efficient method for parametric yield optimization of MOS integrated circuits.

Tat-Kwan Yu, Sung-Mo Kang, Jerome Sacks, William J. Welch

Proceedings of the 1989 IEEE International Conference on Computer-Aided Design, 1989