25 citations · 70 across the 17 of their papers we have counts for
17 papers
Bayesian Optimization in Linear Time
Jesse Schneider, William J. Welch
Bayesian optimization is a sequential method for minimizing objective functions that are expensive to evaluate and about which few assumptions can be made. By using all gathered da…
Data-Adaptive Dimensional Analysis for Accurate Interpolation and Extrapolation in Computer Experiments
G. Alexi Rodriguez-Arelis, William J. Welch
Dimensional analysis (DA) pays attention to fundamental physical dimensions such as length and mass when modelling scientific and engineering systems. It goes back at least a centu…
A Gaussian Sliding Windows Regression Model for Hydrological Inference
Stefan Schrunner, Parham Pishrobat, Joseph Janssen +4
Statistical models are an essential tool to model, forecast and understand the hydrological processes in watersheds. In particular, the understanding of time lags associated with t…
Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science
Joseph Janssen, Shizhe Meng, Asad Haris +5
Scientists and statisticians often want to learn about the complex relationships that connect two time-varying variables. Recent work on sparse functional historical linear models…
Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression
Xin Ding, Yongwei Wang, Zuheng Xu +2
Knowledge distillation (KD) has been actively studied for image classification tasks in deep learning, aiming to improve the performance of a student based on the knowledge from a…
Efficient Subsampling of Realistic Images From GANs Conditional on a Class or a Continuous Variable
Xin Ding, Yongwei Wang, Z. Jane Wang +1
Recently, subsampling or refining images generated from unconditional GANs has been actively studied to improve the overall image quality. Unfortunately, these methods are often ob…
Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms
Xin Ding, Yongwei Wang, Zuheng Xu +2
This work proposes the continuous conditional generative adversarial network (CcGAN), the first generative model for image generation conditional on continuous, scalar conditions (…
Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images based on Annotation-free Training Samples
Xin Ding, Qiong Zhang, William J. Welch
Modern methods often formulate the counting of cells from microscopic images as a regression problem and more or less rely on expensive, manually annotated training images (e.g., d…
Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space with Softplus Loss
Xin Ding, Z. Jane Wang, William J. Welch
Filtering out unrealistic images from trained generative adversarial networks (GANs) has attracted considerable attention recently. Two density ratio based subsampling methods---Di…
Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile
Hao Chen, William J. Welch
A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or…
Adaptive Partitioning Design and Analysis for Emulation of a Complex Computer Code
Sonja Surjanovic, William J. Welch
Computer models are used as replacements for physical experiments in a large variety of applications. Nevertheless, direct use of the computer model for the ultimate scientific obj…
Bayesian Optimization Using Monotonicity Information and Its Application in Machine Learning Hyperparameter
Wenyi Wang, William J. Welch
We propose an algorithm for a family of optimization problems where the objective can be decomposed as a sum of functions with monotonicity properties. The motivating problem is op…
Regression Phalanxes
Hongyang Zhang, William J. Welch, Ruben H. Zamar
Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work we…
Ensembles of phalanxes across assessment metrics for robust ranking of homologous proteins
Jabed H Tomal, William J Welch, Ruben H Zamar
Two proteins are homologous if they have a common evolutionary origin, and the binary classification problem is to identify proteins in a candidate set that are homologous to a par…
Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives
Derek Bingham, Pritam Ranjan, William Welch
A computer code or simulator is a mathematical representation of a physical system, for example a set of differential equations. Running the code with given values of the vector of…
Ensembling classification models based on phalanxes of variables with applications in drug discovery
Jabed H. Tomal, William J. Welch, Ruben H. Zamar
Statistical detection of a rare class of objects in a two-class classification problem can pose several challenges. Because the class of interest is rare in the training data, ther…
Efficient, adaptive cross-validation for tuning and comparing models, with application to drug discovery
Hui Shen, William J. Welch, Jacqueline M. Hughes-Oliver
Cross-validation (CV) is widely used for tuning a model with respect to user-selected parameters and for selecting a "best" model. For example, the method of -nearest neighbors…