Simplicial 2-Complex Convolutional Neural Nets
Eric Bunch, Qian You, Glenn Fung, Vikas Singh · arXiv (Cornell University) · 2020
Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph. While useful, graph structures can be potentially limiting. Hypergraph structures in general do not account for higher order relations between their hyperedges. Simplicial complexes offer a middle ground, with a rich theory to draw on. We develop a convolutional neural network layer on simplicial 2-complexes.