Graph Contrastive Learning via Interventional View Generation

Author:

Wo Zengyi1ORCID,Shao Minglai2ORCID,Wang Wenjun1ORCID,Guo Xuan1ORCID,Lin Lu3ORCID

Affiliation:

1. College of Intelligence and Computing, Tianjin University, Tianjin, China

2. School of New Media and Communication, Tianjin University, Tianjin, China

3. The Pennsylvania State University, State College, PA, USA

Publisher

ACM

Reference49 articles.

1. Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, and Aram Galstyan. 2019. Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing. In international conference on machine learning. PMLR, 21--29.

2. Beyond Low-frequency Information in Graph Convolutional Networks

3. Towards Self-supervised Learning on Graphs with Heterophily

4. Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607.

5. Eli Chien, Jianhao Peng, Pan Li, and Olgica Milenkovic. 2020. Adaptive universal generalized pagerank graph neural network. arXiv preprint arXiv:2006.07988 (2020).

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