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 1. [arXiv 2023] **AmGCL: Feature Imputation of Attribute Missing Graph via Self-supervised Contrastive Learning** [[paper]](https://arxiv.org/pdf/2305.03741.pdf)
 1. [arXiv 2023] **SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning** [[paper]](https://arxiv.org/pdf/2305.04501.pdf)
 1. [arXiv 2023] **CSGCL: Community-Strength-Enhanced Graph Contrastive Learning** [[paper]](https://arxiv.org/pdf/2305.04658.pdf)
+1. [TKDE 2023] **Iterative Graph Self-Distillation** [[paper]](https://arxiv.org/abs/2010.12609.pdf)
 1. [TKDE 2023] **MINING: Multi-Granularity Network Alignment Based on Contrastive Learning** [[paper]](https://ieeexplore.ieee.org/abstract/document/10120956)
 1. [ICASSP 2023] **Select The Best: Enhancing Graph Representation with Adaptive Negative Sample Selection** [[paper]](https://ieeexplore.ieee.org/abstract/document/10095586)
 1. [ICASSP 2023] **Graph Contrastive Learning with Learnable Graph Augmentation** [[paper]](https://ieeexplore.ieee.org/abstract/document/10095511)
@@ -398,7 +399,6 @@
  67. [KDD 2021] **Pre-training on Large-Scale Heterogeneous Graph** [[paper]](http://www.shichuan.org/doc/111.pdf)
  68. [KDD 2021] **MoCL: Contrastive Learning on Molecular Graphs with Multi-level Domain Knowledge** [[paper]](https://arxiv.org/pdf/2106.04509.pdf)
  69. [KDD 2021] **Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning** [[paper]](https://arxiv.org/abs/2105.09111) [[code]](https://github.com/liun-online/HeCo)
- 87. [WWW 2021 Workshop] **Iterative Graph Self-Distillation** [[paper]](https://arxiv.org/abs/2010.12609)
  88. [WWW 2021] **HDMI: High-order Deep Multiplex Infomax** [[paper]](https://arxiv.org/abs/2102.07810) [[code]](https://github.com/baoyujing/HDMI)
  89. :fire:[WWW 2021] **Graph Contrastive Learning with Adaptive Augmentation** [[paper]](https://arxiv.org/abs/2010.14945) [[code]](https://github.com/CRIPAC-DIG/GCA)
  90. [WWW 2021] **SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism** [[paper]](https://arxiv.org/abs/2101.08170) [[code]](https://github.com/RingBDStack/SUGAR)