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FINCGAN: A GAN FRAMEWORK OF IMBALANCED NODE CLASSIFICATION ON HETEROGENEOUS GRAPH NEURAL NETWORK

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DOI:
10.60864/r8xy-mr50
Citation Author(s):
Hung Chun Hsu
Hung Chun Hsu, Ting-Le Lin, Bo-Jun Wu, Ming-Yi Hong, Che Lin, Chih-Yu Wang
Submitted by:
Hung Chun Hsu
Last updated:
6 June 2024 - 10:54am
Document Type:
Poster
Document Year:
2024
Event:
IEEE ICASSP 2024
Presenters:
Hung Chun, Hsu
Paper Code:
MLSP-P36.8
Categories:
Machine Learning for Signal Processing
 

We introduce FincGAN, a GAN framework designed to address the class imbalance in GNNs by enhancing minority sample synthesis and ensuring connectivity with sparsity-aware edge generators.

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