Use of Artificial Intelligence in Group Representation Theory

Abstract

In this thesis, we aimed to explore the intersection between artificial intelligence and representation theory. We began by providing a comprehensive overview of the necessary background material, including artificial intelligence and machine learning, neural networks, and graph neural networks, as well as representation theory. To further illustrate the practical 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 theory. We replicated their code and results, with the goal of gaining a