14 citations · 23 across the 3 of their papers we have counts for
3 papers · 1 filter
(K)not machine learning
Jessica Craven, Mark Hughes, Vishnu Jejjala +1
We review recent efforts to machine learn relations between knot invariants. Because these knot invariants have meaning in physics, we explore aspects of Chern-Simons theory and hi…
Learning knot invariants across dimensions
Jessica Craven, Mark Hughes, Vishnu Jejjala +1
We use deep neural networks to machine learn correlations between knot invariants in various dimensions. The three-dimensional invariant of interest is the Jones polynomial ,…
Disentangling a Deep Learned Volume Formula
Jessica Craven, Vishnu Jejjala, Arjun Kar
We present a simple phenomenological formula which approximates the hyperbolic volume of a knot using only a single evaluation of its Jones polynomial at a root of unity. The avera…