Understand
The performance of graph neural nets (GNNs) is known to gradually decrease with increasing number of layers.
- This decay is partly attributed to oversmoothing, where repeated graph convolutions eventually make node embeddings indistinguishable.
- We take a closer look at two different interpretations, aiming to quantify oversmoothing.
- Our main contribution is PairNorm, a novel normalization layer that is based on a careful analysis of the graph convolution operator, which prevents all node embeddings from becoming too similar.
Reading the bibliography…