Exploring Patterns and Relations in Knot Theory by Using Machine Learning

Abstract

. Machine learning is a sub-domain of AI which has manifested impressive applicability in various scientific domains, and provides different techniques that could be used to identify relations or patterns in the data. Machine learning could be used in multiple ways in analyzing and exploring knot theory. In this thesis, we will discuss how machine learning techniques could be used to find relations in knot theory, particularly, how it could be used to discover relations in different knot invariants. Briefly, given a training set {x