Machine-learning classifiers, especially a multi-head attention model, correctly identify almost all free Z2, Z3, Z4, and Z2xZ2 quotients of CICYs on held-out manifolds, with only three missed Z2xZ2 cases.
Polytopes and Machine Learning
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abstract
We introduce machine learning methodology to the study of lattice polytopes. With supervised learning techniques, we predict standard properties such as volume, dual volume, reflexivity, etc, with accuracies up to 100%. We focus on 2d polygons and 3d polytopes with Pl\"ucker coordinates as input, which out-perform the usual vertex representation.
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Machine Learning Free Quotients of CICYs
Machine-learning classifiers, especially a multi-head attention model, correctly identify almost all free Z2, Z3, Z4, and Z2xZ2 quotients of CICYs on held-out manifolds, with only three missed Z2xZ2 cases.