Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distance-wise Prototypical Graph Neural Network in Node Imbalance
  Classification   Recent years have witnessed the significant success of applying graph neural
networks (GNNs) in learning effective node representations for classification.
However, current GNNs are mostly built under the balanced data-splitting, which
is inconsistent with many real-world networks where the number of training
nodes can be extremely imbalanced among the classes. Thus, directly utilizing
current GNNs on imbalanced data would generate coarse representations of nodes
in minority classes and ultimately compromise the classification performance.
This therefore portends the importance of developing effective GNNs for
handling imbalanced graph data. In this work, we propose a novel Distance-wise
Prototypical Graph Neural Network (DPGNN), which proposes a class
prototype-driven training to balance the training loss between majority and
minority classes and then leverages distance metric learning to differentiate
the contributions of different dimensions of representations and fully encode
the relative position of each node to each class prototype. Moreover, we design
a new imbalanced label propagation mechanism to derive extra supervision from
unlabeled nodes and employ self-supervised learning to smooth representations
of adjacent nodes while separating inter-class prototypes. Comprehensive node
classification experiments and parameter analysis on multiple networks are
conducted and the proposed DPGNN almost always significantly outperforms all
other baselines, which demonstrates its effectiveness in imbalanced node
classification. The implementation of DPGNN is available at
\url{https://github.com/YuWVandy/DPGNN}.

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The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
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The categories of this paper are: q-fin
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The categories of this paper are: cond-mat
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org