Jorge Daniel Aguero Quinteros | 2025 I.S. Symposium

Name: Jorge Daniel Aguero Quinteros
Title: Exploiting Symmetries in Training Convolutional Neural Networks
Majors: Mathematics, Computer Science
Advisors: Robert Kelvey; John Musgrave

The fields of Deep Learning and Abstract algebra are connected by the theory of symmetry groups. Convolutional Neural Network Layers are equivariant with respect to translations of an input image. Group Convolutional Networks are a generalization of regular CNN’s that are equivariant to the action of a general Group. I reproduce experiments that confirm an increase in performance of a CNN architecture by replacing convolutions with group convolutions.

Posted in Symposium 2025 on May 1, 2025.