533 citations · 836 across the 28 of their papers we have counts for
4 papers · 1 filter
Learning Topological Invariance
James Halverson, Fabian Ruehle
Two geometric spaces are in the same topological class if they are related by certain geometric deformations. We propose machine learning methods that automate learning of topologi…
On the Learnability of Knot Invariants: Representation, Predictability, and Neural Similarity
Audrey Lindsay, Fabian Ruehle
We analyze different aspects of neural network predictions of knot invariants. First, we investigate the impact of different knot representations on the prediction of invariants an…
Searching for ribbons with machine learning
Sergei Gukov, James Halverson, Ciprian Manolescu +1
We apply Bayesian optimization and reinforcement learning to a problem in topology: the question of when a knot bounds a ribbon disk. This question is relevant in an approach to di…
Learning to Unknot
Sergei Gukov, James Halverson, Fabian Ruehle +1
We introduce natural language processing into the study of knot theory, as made natural by the braid word representation of knots. We study the UNKNOT problem of determining whethe…