Papers › Geometric deep learning approach to knot theory
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.
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