Xunqiang Jiang

2 accepted papers

2021

CuCo: Graph Representation with Curriculum Contrastive Learning

Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang

IJCAI 2021poster

Graph-level representation learning is to learn low-dimensional representation for the entire graph, which has shown a large impact on real-world applications. Recently, limited by expensive labeled data, contrastive learning based graph-level representation learning attracts considerable attention.…

Cited by 115 Source ↗PDF ↗Scholar ↗

2021

Learning to Pre-train Graph Neural Networks

Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi

AAAI 2021technical

Graph neural networks (GNNs) have become the defacto standard for representation learning on graphs, which derive effective node representations by recursively aggregating information from graph neighborhoods. While GNNs can be trained from scratch, pre-training GNNs to learn transferable knowledge…

Cited by 154 Source ↗PDF ↗code ↗Scholar ↗