Inverse Estimation of Elastic Modulus Using Physics-Informed Generative Adversarial Networks. - James E. Warner; Julian Cuevas; Geoffrey F. Bomarito; Patrick E. Leser; William P. Leser (CoRR, 2020)

Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression. - Geoffrey F. Bomarito; Patrick E. Leser; N. C. M. Strauss; K. M. Garbrecht; Jacob D. Hochhalter (GECCO Companion, 2022)

Bingo: a customizable framework for symbolic regression with genetic programming. - David L. Randall; Tyler S. Townsend; Jacob D. Hochhalter; Geoffrey F. Bomarito (GECCO Companion, 2022)

Automated Learning of Interpretable Models with Quantified Uncertainty. - Geoffrey F. Bomarito; Patrick E. Leser; N. C. M. Strauss; K. M. Garbrecht; Jacob D. Hochhalter (CoRR, 2022)

On the optimization of approximate control variates with parametrically defined estimators. - Geoffrey F. Bomarito; Patrick E. Leser; James E. Warner; William P. Leser (J. Comput. Phys., 2022)

Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations. - Hongsup Oh; Roman Amici; Geoffrey F. Bomarito; Shandian Zhe; Robert M. Kirby; Jacob D. Hochhalter (CoRR, 2023)

Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. - Patrick E. Leser; Geoffrey F. Bomarito; Gabriel Kronberger; Fabrício Olivetti de França (GECCO Companion, 2024)

Covariance Expressions for Multifidelity Sampling with Multioutput, Multistatistic Estimators: Application to Approximate Control Variates. - Thomas O. Dixon; James E. Warner; Geoffrey F. Bomarito; Alex A. Gorodetsky (SIAM/ASA J. Uncertain. Quantification, 2024)

Inherently interpretable machine learning solutions to differential equations. - Hongsup Oh; Roman Amici; Geoffrey F. Bomarito; Shandian Zhe; Robert M. Kirby; Jacob D. Hochhalter (Eng. Comput., 2024)

Call for Action: towards the next generation of symbolic regression benchmark. - Guilherme Seidyo Imai Aldeia; Hengzhe Zhang; Geoffrey F. Bomarito; Miles D. Cranmer; Alcides Fonseca; Bogdan Burlacu; William G. La Cava; Fabrício Olivetti de França (CoRR, 2025)

Generative Modeling of Random Fields from Limited Data via Constrained Latent Flow Matching. - James E. Warner; Tristan A. Shah; Patrick E. Leser; Geoffrey F. Bomarito; Joshua D. Pribe; Michael C. Stanley (CoRR, 2025)