Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Measuring and Relieving the Over-smoothing Problem for Graph Neural
  Networks from the Topological View   Graph Neural Networks (GNNs) have achieved promising performance on a wide
range of graph-based tasks. Despite their success, one severe limitation of
GNNs is the over-smoothing issue (indistinguishable representations of nodes in
different classes). In this work, we present a systematic and quantitative
study on the over-smoothing issue of GNNs. First, we introduce two quantitative
metrics, MAD and MADGap, to measure the smoothness and over-smoothness of the
graph nodes representations, respectively. Then, we verify that smoothing is
the nature of GNNs and the critical factor leading to over-smoothness is the
low information-to-noise ratio of the message received by the nodes, which is
partially determined by the graph topology. Finally, we propose two methods to
alleviate the over-smoothing issue from the topological view: (1) MADReg which
adds a MADGap-based regularizer to the training objective;(2) AdaGraph which
optimizes the graph topology based on the model predictions. Extensive
experiments on 7 widely-used graph datasets with 10 typical GNN models show
that the two proposed methods are effective for relieving the over-smoothing
issue, thus improving the performance of various GNN models.

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The categories of this paper are: math
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin