7 citations · 20 across the 9 of their papers we have counts for
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cs.NE2023★ 5 cited
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Jintang Li, Huizhe Zhang, Ruofan Wu +5
While contrastive self-supervised learning has become the de-facto learning paradigm for graph neural networks, the pursuit of higher task accuracy requires a larger hidden dimensi…
cs.DC2023
Massively Parallel Single-Source SimRanks in Rounds
Siqiang Luo, Zulun Zhu
SimRank is one of the most fundamental measures that evaluate the structural similarity between two nodes in a graph and has been applied in a plethora of data management tasks. Th…