Before revision: In order to overcome the expressive limitations of graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.
After revision: The lack of anisotropic kernels in graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.