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Graph entropy minimization for semi-supervised node classification
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DOI：10.1016/j.neucom.2025.132359.png)
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Abstract
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• We prove that entropy minimization facilitates information propagation in graphs. • We propose node classifiers that are accurate, memory-efficient and fast. • We address multiple real-world concerns in node classification simultaneously.
Journal
IF:
6.5
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2.5W
Citations:
6.5W