Narrowing the Gap between Combinatorial and Hyperbolic Knot Invariants via Deep Learning

Abstract

We present a statistical approach for the discovery of relationships between mathematical entities that is based on linear regression and deep learning with fully connected artificial neural networks. The strategy is applied to computational knot data and empirical connections between combinatorial and hyperbolic knot invariants are revealed.

17 pages, 1 figure

References in corpus (3)

• Array Programming with NumPy
• Deep Learning the Hyperbolic Volume of a Knot
• Disentangling a Deep Learned Volume Formula