Analyzing embedded simplicial complexes, such as triangular meshes and graphs, is an important problem in many fields. We propose a new approach for analyzing embedded simplicial complexes in a subdivision-invariant and isometry-invariant way using only topological and geometric information. Our approach is based on creating and analyzing sufficient statistics and uses a graph neural network. We demonstrate the effectiveness of our approach using a synthetic mesh data set.

翻译：分析嵌入的简易综合体,如三角环形和图解,是许多领域的一个重要问题。我们建议采用一种新办法,仅使用地形和几何信息,在亚vision-异差和同位素-异变方式中分析嵌入的简化综合体。我们的方法是建立和分析足够的统计数据,并使用图形神经网络。我们用合成网格数据集来展示我们的方法的有效性。</s>