论文标题
机器学习多层的尺寸
Machine Learning the Dimension of a Polytope
论文作者
论文摘要
我们使用机器学习来直接从其Ehrhart系列中预测晶格多层的尺寸。这是非常有效的，可实现几乎100％的准确性。我们还使用机器学习从其Ehrhart系列中恢复了晶格多层的体积，并从其Ehrhart系列中恢复了理性多层的维度，体积和准期。在每种情况下，我们都能达到很高的精度，并且我们提出了数学解释，以说明为什么这样做。
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.
