43 citations · 108 across the 22 of their papers we have counts for
Showing 2022 · cs.LGShow all
2 papers · 2 filters
cs.LG2022★ 2 cited
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes
Wei Duan, Junyu Xuan, Maoying Qiao +1
Graph convolutional networks (GCNs) have achieved great success in graph representation learning by extracting high-level features from nodes and their topology. Since GCNs general…
cs.LG2022★ 43 cited
Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples
Wei Duan, Junyu Xuan, Maoying Qiao +1
Graph Convolutional Neural Networks (GCNs) has been generally accepted to be an effective tool for node representations learning. An interesting way to understand GCNs is to think…