Abstract

The fields of Deep Learning and Abstract algebra are connected by the theory of symmetry groups. Convolutional Neural Network Layers are equiariant with respect to translations of an input image. Group Convolutional Networks are an 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.

Advisor

Kelvey, Robert

Department

Computer Science; Mathematics

Disciplines

Algebra | Artificial Intelligence and Robotics

Publication Date

2025

Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis

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