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)

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)

Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. - Fabrício Olivetti de França; Marco Virgolin; Michael Kommenda; Maimuna S. Majumder; Miles D. Cranmer; Guilherme Espada; Leon Ingelse; Alcides Fonseca; Mikel Landajuela; Brenden K. Petersen; Ruben Glatt; T. Nathan Mundhenk; et al. (CoRR, 2023)

Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. - Zachary Bastiani; Robert M. Kirby; Jacob D. Hochhalter; Shandian Zhe (CoRR, 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)

Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data. - Keyan Chen; Yile Li; Da Long; Zhitong Xu; Wei Xing; Jacob D. Hochhalter; Shandian Zhe (CoRR, 2025)

Diffusion-Based Symbolic Regression. - Zachary Bastiani; Robert M. Kirby; Jacob D. Hochhalter; Shandian Zhe (CoRR, 2025)

SIFBench: An Extensive Benchmark for Fatigue Analysis. - Tushar Gautam; Robert M. Kirby; Jacob D. Hochhalter; Shandian Zhe (CoRR, 2025)

SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation. - Fabrício Olivetti de França; Marco Virgolin; Michael Kommenda; Maimuna S. Majumder; Miles D. Cranmer; Guilherme Espada; Leon Ingelse; Alcides Fonseca; Mikel Landajuela; Brenden K. Petersen; Ruben Glatt; T. Nathan Mundhenk; et al. (IEEE Trans. Evol. Comput., 2025)