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GRAPHULY: GRAPH U-Nets-Based Multi-Level Graph LaYout

Kai YAN, Tiejun ZHAO, Muyun YANG

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Summary :

Graph layout is a critical component in graph visualization. This paper proposes GRAPHULY, a graph u-nets-based neural network, for end-to-end graph layout generation. GRAPHULY learns the multi-level graph layout process and can generate graph layouts without iterative calculation. We also propose to use Laplacian positional encoding and a multi-level loss fusion strategy to improve the layout learning. We evaluate the model with a random dataset and a graph drawing dataset and showcase the effectiveness and efficiency of GRAPHULY in graph visualization.

Publication
IEICE TRANSACTIONS on Information Vol.E105-D No.12 pp.2135-2138
Publication Date
2022/12/01
Publicized
2022/09/16
Online ISSN
1745-1361
DOI
10.1587/transinf.2022EDL8050
Type of Manuscript
LETTER
Category
Computer Graphics

Authors

Kai YAN
  Harbin Institute of Technology
Tiejun ZHAO
  Harbin Institute of Technology
Muyun YANG
  Harbin Institute of Technology

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