PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by\n Partial Differential Equations

Graph neural networks are increasingly becoming the go-to approach in various\nfields such as computer vision, computational biology and chemistry, where data\nare naturally explained by graphs. However, unlike traditional convolutional\nneural networks, deep graph networks do not necessarily yield ... View More