59 citations · 245 across the 14 of their papers we have counts for
3 papers · 1 filter
Deep Graph Neural Networks with Shallow Subgraph Samplers
Hanqing Zeng, Muhan Zhang, Yinglong Xia +6
While Graph Neural Networks (GNNs) are powerful models for learning representations on graphs, most state-of-the-art models do not have significant accuracy gain beyond two to thre…
The LDBC Graphalytics Benchmark
Alexandru Iosup, Ahmed Musaafir, Alexandru Uta +15
In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective compa…
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning
Muhan Zhang, Pan Li, Yinglong Xia +2
In this paper, we provide a theory of using graph neural networks (GNNs) for multi-node representation learning (where we are interested in learning a representation for a set of m…