Geometric deep learning approach to knot theory
Lennart Jaretzki
In this paper, we introduce a novel way to use geometric deep learning for
knot data by constructing a functor that takes knots to graphs and using graph
neural networks. We will attempt to predict several knot invariants with this
approach. This approach demonstrates high generalization capabilities.