Francis J. Alexander

Orcid: 0000-0001-9848-555X

According to our database1, Francis J. Alexander authored at least 26 papers between 2005 and 2024.

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Bibliography

2024
Multi-objective latent space optimization of generative molecular design models.
Patterns, 2024

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation.
Frontiers Bioinform., 2024

2023
Optimal decision-making in high-throughput virtual screening pipelines.
Patterns, November, 2023

Accelerating scientific discoveries through data-driven innovations.
Patterns, November, 2023

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction.
J. Comput. Biol., July, 2023

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge.
CoRR, 2023

A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows.
CoRR, 2023

Automated Extraction of Molecular Interactions and Pathway Knowledge using Large Language Model, Galactica: Opportunities and Challenges.
Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023

2022
Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning.
Patterns, 2022

Adaptive Group Testing with Mismatched Models.
Proceedings of the IEEE International Conference on Acoustics, 2022

Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
Co-design Center for Exascale Machine Learning Technologies (ExaLearn).
Int. J. High Perform. Comput. Appl., 2021

Efficient Active Learning for Gaussian Process Classification by Error Reduction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Uncertainty-aware Active Learning for Optimal Bayesian Classifier.
Proceedings of the 9th International Conference on Learning Representations, 2021

Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Model-Based Robust Filtering and Experimental Design for Stochastic Differential Equation Systems.
IEEE Trans. Signal Process., 2020

Optimal Bounds on Nonlinear Partial Differential Equations in Model Certification, Validation, and Experimental Design.
CoRR, 2020

2015
Open Simulation Laboratories [Guest editors' introduction].
Comput. Sci. Eng., 2015

Small data is the problem.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014
Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation.
J. Comput. Phys., 2014

2013
Machine Learning.
Comput. Sci. Eng., 2013

2011
Big Data [Guest editorial].
Comput. Sci. Eng., 2011

2008
A Control Variate Approach for Improving Efficiency of Ensemble Monte Carlo
CoRR, 2008

2005
Guest Editors' Introduction: Multiphysics Modeling.
Comput. Sci. Eng., 2005

Adaptive mesh refinement for multiscale nonequilibrium physics.
Comput. Sci. Eng., 2005

Noise in algorithm refinement methods.
Comput. Sci. Eng., 2005


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