Nathan Haut

According to our database, Nathan Haut authored at least 5 papers between 2022 and 2023.

Collaborative distances:

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

2023

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

Nathan Haut, Wolfgang Banzhaf, Bill Punch

CoRR, 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

Correlation versus RMSE Loss Functions in Symbolic Regression Tasks.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

CoRR, 2022

Active Learning Improves Performance on Symbolic RegressionTasks in StackGP.

Nathan Haut, Wolfgang Banzhaf, Bill Punch

CoRR, 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