| 2026 | GECCO | GPU Genetic Programming and the Beagle System. | Nathan Haut, Wolfgang Banzhaf, Ilya Basin |
| 2026 | GECCO | GPU Acceleration of Genetic Programming for Symbolic Regression with the Beagle System. | Nathan Haut, Ilya Basin, Marzieh Kianinejad, Ruchika Gupta, Elijah Smith, Zach Perrico, Wolfgang Banzhaf |
| 2026 | GECCO | Genetic Programming-Based Modeling of Systems of Differential Equations. | Nathan Haut, Stuart W. Card, Mark E. Kotanchek |
| 2025 | GECCO | A Symbolic Hessian-Based Approach for Assessing Model Complexity in Symbolic Regression. | Nathan Haut, Stuart W. Card, Mark E. Kotanchek |
| 2025 | GECCO | Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models. | Nathan Haut, Zenas Huang, Adam Alessio |
| 2025 | GECCO | Rewarding Model Smoothness and Simplicity via Alternating Objectives in Symbolic Regression. | Nathan Haut, Mark E. Kotanchek |
| 2024 | CEC | Data Sampling via Active Learning in Cartesian Genetic Programming for Biomedical Data. | Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc |
| 2024 | PPSN | Adaptive Sampling of Biomedical Images with Cartesian Genetic Programming. | Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc |
| 2023 | GECCO | Active Learning Informs Symbolic Regression Model Development in Genetic Programming. | Nathan Haut, Bill Punch, Wolfgang Banzhaf |
| 2022 | GECCO | Active learning improves performance on symbolic regression tasks in StackGP. | Nathan Haut, Wolfgang Banzhaf, Bill Punch |