Oct 21, 2023 · In this paper, we use simplicial complexes to extract higher-order relations containing multiple nodes from heterogeneous graphs.
Oct 21, 2023 · In this paper, we use simplicial complexes to extract higher-order relations containing multiple nodes from heterogeneous graphs. We also ...
The real world involves many graphs and networks that are essentially heterogeneous, in which various types of relations connect multiple types of vertices.
Apr 15, 2024 · We propose Hyperbolic Heterogeneous Graph Attention Networks (HHGAT) that learn vector representations in hyperbolic spaces with metapath instances.
Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs. J. Li, Y ... Multi-attributed heterogeneous graph convolutional network for bot detection[J].
In this paper, we propose a heterogeneous network representation learning model based on role feature extraction, called HRFE.
Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs. Conference Paper. Oct 2023. Junlin Li · Sun Yueheng · Minglai Shao · View.
A general framework for graph-level clustering, scaling up dynamic graph representation learning via spiking neural networks, generalizing downsampling from ...
An Adaptive Curvature Exploration Hyperbolic Graph Neural Network named ACE-HGNN is proposed to adaptively learn the optimal curvature according to the input ...
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Multi-Order Relations. Hyperbolic Fusion for Heterogeneous Graphs. In Proceedings of the. 32nd ACM International Conference on Information and Knowledge.