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Found 4 papers, 2 papers with code
Multi-view Graph Structural Representation Learning via Graph Coarsening
Specifically, we build three unique views, original, coarsening, and conversion, to learn a thorough structural representation.
HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction
In this paper, we propose HGWaveNet, a novel hyperbolic graph neural network that fully exploits the fitness between hyperbolic spaces and data distributions for temporal link prediction.
H2TNE: Temporal Heterogeneous Information Network Embedding in Hyperbolic Spaces
Temporal heterogeneous information network (temporal HIN) embedding, aiming to represent various types of nodes of different timestamps into low dimensional spaces while preserving structural and semantic information, is of vital importance in diverse real-life tasks.
PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation
However, the application value of SG on downstream tasks is severely limited by the predicate classification bias, which is caused by long-tailed data and presented as semantic bias of predicted relation predicates.
