Jinhao Gu

ORCID: 0000-0003-4041-0429
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About
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Research Areas
  • Machine Learning in Materials Science
  • Advanced Graph Neural Networks
  • Advanced Optical Network Technologies
  • Complex Network Analysis Techniques
  • Network Traffic and Congestion Control
  • Graph Theory and Algorithms

University of Liverpool
2024

This paper proposes a metric to measure the dissimilarity between graphs that may have different number of nodes. The proposed extends generalised optimal subpattern assignment (GOSPA) metric, which is for sets, graphs. graph GOSPA includes costs associated with node attribute errors properly assigned nodes, missed and false nodes edge mismatches computation this based on finding assignments in two graphs, possibility leaving some unassigned. We also propose lower bound computable polynomial...

10.48550/arxiv.2311.07596 preprint EN other-oa arXiv (Cornell University) 2023-01-01
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