Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering. (arXiv:2107.04755v3 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2107.04755

Graph convolutional networks are becoming indispensable for deep learning
from graph-structured data. Most of the existing graph convolutional networks
share two big shortcomings. First, they are essentially low-pass filters, thus
the potentially useful middle and high frequency band of graph signals are
ignored. Second, the bandwidth of existing graph convolutional filters is
fixed. Parameters of a graph convolutional filter only transform the graph
inputs without changing the curvature of a graph convolutional filter function.
In reality, we are uncertain about …

arxiv filtering graph lg networks