Nathaniel Haut

According to our database, Nathaniel Haut authored at least 11 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Sharpness-Aware Minimization in Genetic Programming.

Illya Bakurov, Nathan Haut, Wolfgang Banzhaf

CoRR, 2024

Adaptive Sampling of Biomedical Images with Cartesian Genetic Programming.

Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Dynamically Sampling biomedical Images For Genetic Programming.

Yuri Lavinas, Nathaniel Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Data Sampling via Active Learning in Cartesian Genetic Programming for Biomedical Data.

Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic Regression.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

CoRR, 2023

Accelerating Image Analysis Research with Active Learning Techniques in Genetic Programming.

Nathan Haut, Wolfgang Banzhaf, Bill Punch, Dirk Colbry

Proceedings of the Genetic Programming Theory and Practice XX [GPTP 2023], 2023

Active Learning Informs Symbolic Regression Model Development in Genetic Programming.

Nathan Haut, Bill Punch, Wolfgang Banzhaf

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

Active Learning Improves Performance on Symbolic RegressionTasks in StackGP.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

CoRR, 2022

Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

Proceedings of the Genetic Programming Theory and Practice XIX [GPTP 2022], 2022

Active learning improves performance on symbolic regression tasks in StackGP.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

Back to the Future - Revisiting OrdinalGP and Trustable Models After a Decade.

Mark E. Kotanchek, Nathan Haut

Proceedings of the Genetic Programming Theory and Practice XVIII [GPTP 2021]., 2021