Generating Reflexive Polytopes via Sequence Modeling
Bernt Ivar Utstøl Nødland
Abstract
We train neural network sequence models to generate reflexive lattice polytopes. We demonstrate that they can generate mathematical objects satisfying various geometric properties. We use the completeness of our datasets to give evidence that the models are understanding some underlying structure of the data.
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