arXiv:2210.01301
GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction
원문 초록
In this paper, we propose a Graph Inception Diffusion Networks(GIDN) model. This model generalizes graph diffusion in different feature spaces, and uses the inception module to avoid the large amount of computations caused by complex network structures. We evaluate GIDN model on Open Graph Benchmark(OGB) datasets, reached an 11% higher performance than AGDN on ogbl-collab dataset.
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Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
Demystifying Distributed Training of Graph Neural Networks for Link Prediction
Learnable Spatial-Temporal Positional Encoding for Link Prediction
A Survey of Link Prediction in N-ary Knowledge Graphs
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
GenIC: An LLM-Based Framework for Instance Completion in Knowledge Graphs
토론
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