Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
Papers about self-supervised learning on Graph Neural Networks (GNNs). If you feel there are papers with related topics missing, do not hesitate to let us know (via issues or pull requests).
(implicitly using self-supersvied learning or applying graph neural networks in other domains) 1. [Arxiv 2020] Self-supervised Learning: Generative or Contrastive. [paper] 1. [KDD 2020] Octet: Online Catalog Taxonomy Enrichment with Self-Supervision. [paper] 1. [WWW 2020] Structural Deep Clustering Network. [paper] [code] 1. [ICLR 2020] InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization. [paper] [code] 1. [ICLR 2019] Deep Graph Informax. [paper] [code] 1. [IJCAI 2019] Pre-training of Graph Augmented Transformers for Medication Recommendation. [paper] [code] 1. [Arxiv 2019] Heterogeneous Deep Graph Infomax [paper] [code] 1. [AAAI 2020] Unsupervised Attributed Multiplex Network Embedding [paper] [code] 1. [WWW 2020] Graph representation learning via graphical mutual information maximization [paper] 1. [NeurIPS 2017] Inductive Representation Learning on Large Graphs [paper] [code] 1. [NeurIPS 2016 Workshop] Variational Graph Auto-Encoders [paper] [code] 1. [WWW 2015] LINE: Large-scale Information Network Embedding [paper] [code] 1. [KDD 2014] DeepWalk: Online Learning of Social Representations [paper] [code]