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Found 3 papers, 2 papers with code
Cooperative Network Learning for Large-Scale and Decentralized Graphs
Here, we introduce a Cooperative Network Learning (CNL) framework to ensure secure graph computing for various graph tasks.
Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes
Despite the recent successes of vanilla Graph Neural Networks (GNNs) on various tasks, their foundation on pairwise networks inherently limits their capacity to discern latent higher-order interactions in complex systems.
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Influential Simplices Mining via Simplicial Convolutional Network
It can tackle higher-order tasks by leveraging novel higher-order presentations: hierarchical bipartite graphs and higher-order hierarchical (HoH) Laplacians, where targeted simplices are grouped into a hub set and can interact with other simplices.
