Noise in algorithm refinement methods. - Francis J. Alexander; Daniel M. Tartakovsky; Alejandro L. Garcia (Comput. Sci. Eng., 2005)

Adaptive mesh refinement for multiscale nonequilibrium physics. - Daniel F. Martin; Phillip Colella; Marian Anghel; Francis J. Alexander (Comput. Sci. Eng., 2005)

Guest Editors' Introduction: Multiphysics Modeling. - Daniel M. Tartakovsky; Francis J. Alexander (Comput. Sci. Eng., 2005)

A Control Variate Approach for Improving Efficiency of Ensemble Monte Carlo - Tarik Borogovac; Francis J. Alexander; Pirooz Vakili (CoRR, 2008)

Big Data [Guest editorial]. - Francis J. Alexander; Adolfy Hoisie; Alexander S. Szalay (Comput. Sci. Eng., 2011)

Machine Learning. - Francis J. Alexander (Comput. Sci. Eng., 2013)

Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation. - Søren Taverniers; Francis J. Alexander; Daniel M. Tartakovsky (J. Comput. Phys., 2014)

Small data is the problem. - Edward R. Dougherty; Lori A. Dalton; Francis J. Alexander (ACSSC, 2015)

Open Simulation Laboratories [Guest editors' introduction]. - Francis J. Alexander; Charles Meneveau (Comput. Sci. Eng., 2015)

Optimal Bounds on Nonlinear Partial Differential Equations in Model Certification, Validation, and Experimental Design. - Mike McKerns; Francis J. Alexander; Kyle S. Hickmann; Timothy John Sullivan; Diane E. Vaughan (CoRR, 2020)

Model-Based Robust Filtering and Experimental Design for Stochastic Differential Equation Systems. - Guang Zhao; Xiaoning Qian; Byung-Jun Yoon; Francis J. Alexander; Edward R. Dougherty (IEEE Trans. Signal Process., 2020)

Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty. - Guang Zhao; Edward R. Dougherty; Byung-Jun Yoon; Francis J. Alexander; Xiaoning Qian (AISTATS, 2021)

Uncertainty-aware Active Learning for Optimal Bayesian Classifier. - Guang Zhao; Edward R. Dougherty; Byung-Jun Yoon; Francis J. Alexander; Xiaoning Qian (ICLR, 2021)

Efficient Active Learning for Gaussian Process Classification by Error Reduction. - Guang Zhao; Edward R. Dougherty; Byung-Jun Yoon; Francis J. Alexander; Xiaoning Qian (NeurIPS, 2021)

Co-design Center for Exascale Machine Learning Technologies (ExaLearn). - Francis J. Alexander; James A. Ang; Jenna A. Bilbrey; Jan Balewski; Tiernan Casey; Ryan Chard; Jong Choi 001; Sutanay Choudhury; Bert J. Debusschere; Anthony M. DeGennaro; Nikoli Dryden; J. Austin Ellis; et al. (Int. J. High Perform. Comput. Appl., 2021)

Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. - Xihaier Luo; Sean McCorkle; Gilchan Park; Vanessa López-Marrero; Shinjae Yoo; Edward R. Dougherty; Xiaoning Qian; Francis J. Alexander; Byung-Jun Yoon (BIBM, 2022)

Adaptive Group Testing with Mismatched Models. - Mingzhou Fan; Byung-Jun Yoon; Francis J. Alexander; Edward R. Dougherty; Xiaoning Qian (ICASSP, 2022)

Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning. - Omar Maddouri; Xiaoning Qian; Francis J. Alexander; Edward R. Dougherty; Byung-Jun Yoon (Patterns, 2022)

Automated Extraction of Molecular Interactions and Pathway Knowledge using Large Language Model, Galactica: Opportunities and Challenges. - Gilchan Park; Byung-Jun Yoon; Xihaier Luo; Vanessa López-Marrero; Patrick R. Johnstone; Shinjae Yoo; Francis J. Alexander (BioNLP@ACL, 2023)

A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows. - Line Pouchard; Kristofer G. Reyes; Francis J. Alexander; Byung-Jun Yoon (CoRR, 2023)

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge. - Gilchan Park; Byung-Jun Yoon; Xihaier Luo; Vanessa López-Marrero; Patrick R. Johnstone; Shinjae Yoo; Francis J. Alexander (CoRR, 2023)

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction. - Puhua Niu; Maria J. Soto; Shuai Huang 001; Byung-Jun Yoon; Edward R. Dougherty; Francis J. Alexander; Ian Blaby; Xiaoning Qian (J. Comput. Biol., 2023)

Accelerating scientific discoveries through data-driven innovations. - Francis J. Alexander; Meifeng Lin; Xiaoning Qian; Byung-Jun Yoon (Patterns, 2023)

Optimal decision-making in high-throughput virtual screening pipelines. - Hyun-Myung Woo; Xiaoning Qian; Li Tan; Shantenu Jha; Francis J. Alexander; Edward R. Dougherty; Byung-Jun Yoon (Patterns, 2023)

Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity. - Mingzhou Fan; Byung-Jun Yoon; Edward R. Dougherty; Nathan M. Urban; Francis J. Alexander; Raymundo Arróyave; Xiaoning Qian (UAI, 2024)

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation. - Xihaier Luo; Seyednami Niyakan; Patrick R. Johnstone; Sean McCorkle; Gilchan Park; Vanessa López-Marrero; Shinjae Yoo; Edward R. Dougherty; Xiaoning Qian; Francis J. Alexander; Shantenu Jha; Byung-Jun Yoon (Frontiers Bioinform., 2024)

Multi-objective latent space optimization of generative molecular design models. - A. N. M. Nafiz Abeer; Nathan M. Urban; M. Ryan Weil; Francis J. Alexander; Byung-Jun Yoon (Patterns, 2024)

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. - Ozan Gökdemir; Carlo Siebenschuh; Alexander Brace; Azton Wells; Brian Hsu; Kyle Hippe; Priyanka Setty; Aswathy Ajith; J. Gregory Pauloski; Varuni Sastry; Sam Foreman; Huihuo Zheng; et al. (PASC, 2025)

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. - Ozan Gökdemir; Carlo Siebenschuh; Alexander Brace; Azton Wells; Brian Hsu; Kyle Hippe; Priyanka Vasanthakumari; Aswathy Ajith; J. Gregory Pauloski; Varuni Katti Sastry; Sam Foreman; Huihuo Zheng; et al. (CoRR, 2025)

Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data. - Lothar Heimbach; Sebastian Kaltenbach; Petr Karnakov; Francis J. Alexander; Petros Koumoutsakos (CoRR, 2025)