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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
| Date | Stars |
|---|---|
| 2026-08-05 | 1727 |
| 2026-08-07 | 1728 |
| 2026-08-10 | 1728 |
| 2026-08-11 | 1728 |
| 2026-08-12 | 1729 |
| 2026-08-18 | 1729 |
| 2026-08-19 | 1730 |
| 2026-08-21 | 1728 |
| 2026-09-18 | 1727 |
| 2026-09-28 | 1726 |
| 2026-10-08 | 1725 |
| 2026-10-10 | 1726 |
| 2026-10-22 | 1727 |
| 2026-11-01 | 1726 |
| 2026-11-03 | 1727 |
| 2026-11-04 | 1727 |
Today
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+1 stars this month
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# awesome-self-supervised-gnn  [](https://awesome.re)   This repository contains a list of papers on the **Self-supervised Learning on Graph Neural Networks (GNNs)**, we categorize them based on their published years. We will try to make this list updated. If you found any error or any missed paper, please don't hesitate to open issues or pull requests. Note: :fire: indicates the paper is extensively cited (e.g., > 80 citations). The code is provided in `get_hot.py`. ## Year 2024 1. [ICASSP 2024] **Contrastive Deep Nonnegative Matrix Factorization for Community Detection** [[paper]](https://arxiv.org/abs/2311.02357) [[code]](https://github.com/6lyc/CDNMF) ## Year 2023 1. [ICLR 2023] **Empowering Graph Representation Learning with Test-Time Graph Transformation** [[paper]](https://openreview.net/forum?id=Lnxl5pr018) [[code]](https://github.com/ChandlerBang/GTrans) 1. [ICLR 2023] **Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization** [[paper]](https://arxiv.org/pdf/2210.02016.pdf) [[code]](https://github.com/jumxglhf/ParetoGNN) 1. [AAAI 2023] **Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning** [[paper]](https://arxiv.org/pdf/2202.08480) [[code]](https://github.com/kaize0409/S-3-CL) 1. [arXiv 2023] **Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection** [[paper]](https://arxiv.org/pdf/2306.00006.pdf) 1. [ICASSP 2023] **Contrastive Learning at the Relation and Event Level for Rumor Detection** [[paper]](https://ieeexplore.ieee.org/abstract/document/10096567) 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] **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) 1. [arXiv 2023] **FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction** [[paper]](https://arxiv.org/pdf/2305.02549.pdf) 1. [INS 2023] **A fairness-aware graph contrastive learning recommender framework for social tagging systems** [[paper]](https://www.sciencedirect.com/science/article/pii/S0020025523006497) 1. [arXiv 2023] **Improving Knowledge Graph Entity Alignment with Graph Augmentation** [[paper]](https://arxiv.org/pdf/2304.14585.pdf) 1. [WWW 2023] **Graph Self-supervised Learning with Augmentation-aware Contrastive Learning** [[paper]](https://dl.acm.org/doi/abs/10.1145/3543507.3583246) 1. [arXiv 2023] **A Systematic Survey of Chemical Pre-trained Models** [[paper]](https://sxkdz.github.io/files/publications/IJCAI/CPM/CPM.pdf) 1. [WWW 2023] **Self-Supervised Teaching and Learning of Representations on Graphs** [[paper]](https://dl.acm.org/doi/abs/10.1145/3543507.3583441) 1. [TKDE 2023] **Progressive Hard Negative Masking: From Global Uniformity to Local Tolerance** [[paper]](https://ieeexplore.ieee.org/abstract/document/10111083) 1. [KBS 2023] **ST-A-PGCL: Spatiotemporal adaptive periodical graph
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yingheng
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Yupeng Hou · Google DeepMind
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Yuecheng Li · Sun Yat-sen University · China
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Shaw · Tsinghua University · China
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yueliu1999 · National University of Singapore · Singapore
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Yuhao · The University of Hong Kong · Hong Kong
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Jinheon Baek
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a995793d0436981f, topic:deep-learning, topic:pretraining, desc:pretraining