Cell complexes are topological spaces constructed from simple blocks called cells. They generalize graphs, simplicial complexes, and polyhedral complexes that form important domains for practical applications. We propose a general, combinatorial, and unifying construction for performing neural network-type computations on cell complexes. Furthermore, we introduce inter-cellular message passing schemes, message passing schemes on cell complexes that take the topology of the underlying space into account. In particular, our method generalizes many of the most popular types of graph neural networks.
翻译:细胞综合体是用简单块块构建的地形空间,称为细胞。它们概括了图形、简易综合体和多面综合体,它们构成了实用应用的重要领域。我们提议在细胞综合体上进行神经网络类型计算时进行一般、组合和统一构建。此外,我们引入了细胞间信息传递计划,以及细胞综合体的信息传递计划,这些计划考虑到了基础空间的地形。特别是,我们的方法概括了许多最受欢迎的图形神经网络类型。