Geometric deep learning approach to knot theory

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Publication date: 26 May 2023

Abstract: 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.

Has companion code repository: https://github.com/lennartjaretzki/geometricdeeplearningknotdata

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