Use of Artificial Intelligence in Group Representation Theory

Abstract

In this thesis, we aimed to explore the intersection between artificial intelligence and repre- sentation theory. We began by providing a comprehensive overview of the necessary back- ground material, including artificial intelligence and machine learning, neural networks, and graph neural networks, as well as representation theory. To further illustrate the prac- tical applications of these techniques, we analyzed a recent paper [9] that leveraged graph neural networks to improve the state-of-the-art in a specific problem in representation the- ory. We replicated their code and results, with the goal of gaining a deeper understanding of the techniques they employed and the insights they gleaned.