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Found 4 papers, 1 papers with code
Dual-Channel Multiplex Graph Neural Networks for Recommendation
Nevertheless, these approaches still grapple with two significant shortcomings: (1) Insufficient modeling and exploitation of the impact of various behavior patterns formed by multiplex relations between users and items on representation learning, and (2) ignoring the effect of different relations in the behavior patterns on the target relation in recommender system scenarios.
Multiplex Heterogeneous Graph Convolutional Network
Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous network data, ranging from link prediction to node classification.
Speed and fate diversity tradeoff in nematode's early embryogenesis
Nematode species are well-known for their invariant cell lineage pattern during development.
Efficiently Detecting Overlapping Communities through Seeding and Semi-Supervised Learning
This paper proposes a new method that transforms a network into a corpus where each edge is treated as a document, and all nodes of the network are treated as terms of the corpus.
