2022/07/15 by Tom Coates, Coates, Tom, Johannes Hofscheier +3 · 1 voice
Computer Science · Engineering · Mathematics · #Advanced Numerical Analysis Techniques #Combinatorics (math.CO) #Data Management and Algorithms #FOS: Mathematics #Handwritten Text Recognition Techniques #math.CO
paper · pdf · doi:10.48550/arxiv.2207.07717
openalex publication_date 2022/07/15 · arxiv published 2022/07/15 · arxiv updated 2022/07/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 Ehrhart series, and to recover the dimension, volume, and quasi-period of a rational polytope from its Ehrhart series. In each case we achieve very high accuracy, and we propose mathematical explanations for why this should be so.