Garrett Bingham
Ph.D. Student
Garrett is a fourth-year Ph.D. student. His research utilizes evolutionary algorithms and meta-learning to optimize deep learning workflows. Prior to UT Austin, Garrett received a B.S. in Computer Science and Mathematics from Yale University.
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks Garrett Bingham and Risto Miikkulainen In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023. (also arXiv:20... 2023

Efficient Activation Function Optimization through Surrogate Modeling Garrett Bingham and Risto Miikkulainen arXiv:2301.05785, 2023. 2023

Discovering Parametric Activation Functions Garrett Bingham and Risto Miikkulainen Neural Networks, 148:48-65, 2022. 2022

Evolutionary Optimization of Deep Learning Activation Functions Garrett Bingham, William Macke, and Risto Miikkulainen In Genetic and Evolutionary Computation Conference (GECCO '20), 289-296, Cancun, Mexico, 20... 2020