All Outputs (2)

Polytopes and machine learning (2023)
Journal Article
Bao, J., He, Y., Hirst, E., Hofscheier, J., Kasprzyk, A., & Majumder, S. (2023). Polytopes and machine learning. International Journal of Data Science in the Mathematical Sciences, 1(2), 181-211. https://doi.org/10.1142/S281093922350003X

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... Read More about Polytopes and machine learning.

Machine Learning: The Dimension of a Polytope (2023)
Book Chapter
Coates, T., Hofscheier, J., & Kasprzyk, A. M. (2023). Machine Learning: The Dimension of a Polytope. In Machine Learning in Pure Mathematics and Theoretical Physics (85-104). World Scientific. https://doi.org/10.1142/9781800613706_0003

We use machine learning to predict the dimension of a lattice polytope directly from its Ehrhart series. This is highly effective, achieving almost 100% accuracy. We also use machine learning to recover the volume of a lattice polytope from its Ehrha... Read More about Machine Learning: The Dimension of a Polytope.