Garrett Bingham
Collaborator
Garrett's PhD research focused on automatic machine learning. Prior to UT Austin, Garrett received a B.S. in Computer Science and Mathematics from Yale University.
Homepage:
https://garrettbingham.com
Publications
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks 2023
Garrett Bingham and Risto Miikkulainen, In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023. (also arXiv:2021.08958).
Efficient Activation Function Optimization through Surrogate Modeling 2023
Garrett Bingham and Risto Miikkulainen, In Proceedings of the 23rd Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.
Optimizing Neural Networks through Activation Function Discovery and Automatic Weight Initialization 2023
Garrett Bingham, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Discovering Parametric Activation Functions 2022
Garrett Bingham and Risto Miikkulainen, Neural Networks, Vol. 148 (2022), pp. 48-65.
Evolutionary Optimization of Deep Learning Activation Functions 2020
Garrett Bingham, William Macke, and Risto Miikkulainen, In Genetic and Evolutionary Computation Conference (GECCO '20), pp. 289-296, Cancun, Mexico, 2020.
Areas of Interest
Evolutionary Computation Neuroevolution Supervised Learning
Labs
Currently affiliated with Neural Networks Formerly affiliated with Neural Networks