| https://github.com/naganandy/graph-based-deep-learning-literature | links to conference publications in graph-based deep learning (Very, Very, Very Important) |
| https://github.com/SherylHYX/pytorch_geometric_signed_directed | PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. |
| https://github.com/EdisonLeeeee/Awesome-Fair-Graph-Learning | Paper Lists for Fair Graph Learning |
| https://github.com/thunlp/PromptPapers | Must-read papers on prompt-based tuning for pre-trained language models. |
| https://github.com/zhao-tong/graph-data-augmentation-papers | A curated list of graph data augmentation papers. |
| https://github.com/Thinklab-SJTU/ThinkMatch | Code & pretrained models of novel deep graph matching methods. |
| https://github.com/FLHonker/Awesome-Knowledge-Distillation | Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。 |
| https://github.com/zlpure/awesome-graph-representation-learning | A curated list for awesome graph representation learning resources. |
| https://github.com/basiralab/GNNs-in-Network-Neuroscience | A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020. |
| https://github.com/flyingdoog/awesome-graph-explainability-papers | Papers about explainability of GNNs |
| https://github.com/yuanqidu/awesome-graph-generation | A curated list of graph generation papers and resources. |
| https://github.com/benedekrozemberczki/awesome-decision-tree-papers | A collection of research papers on decision, classification and regression trees with implementations. |
| https://github.com/AstraZeneca/awesome-explainable-graph-reasoning | A collection of research papers and software related to explainability in graph machine learning. |
| https://github.com/LirongWu/awesome-graph-self-supervised-learning | Awesome Graph Self-Supervised Learning |
| https://github.com/Chen-Cai-OSU/awesome-equivariant-network | Paper list for equivariant neural network |
| https://github.com/mengliu1998/DL4DisassortativeGraphs | Papers about developing DL methods on disassortative graphs |
| https://github.com/SunQingYun1996/Graph-Reinforcement-Learning-Papers | A curated list of graph reinforcement learning papers. |
| https://github.com/ChandlerBang/awesome-self-supervised-gnn | Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN). |
| https://github.com/GRAND-Lab/Awesome-Graph-Neural-Networks | Paper Lists for Graph Neural Networks |
| https://github.com/jwzhanggy/IFMLab_GNN | Graph Neural Network Models from IFM Lab |
| https://github.com/ChandlerBang/awesome-graph-attack-papers | Adversarial attacks and defenses on Graph Neural Networks. |
| https://github.com/safe-graph/graph-adversarial-learning-literature | A curated list of adversarial attacks and defenses papers on graph-structured data. |
| https://github.com/benedekrozemberczki/awesome-graph-classification | A collection of important graph embedding, classification and representation learning papers with implementations. |
| https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers | A curated list of gradient boosting research papers with implementations. |
| https://github.com/benedekrozemberczki/awesome-community-detection | A curated list of community detection research papers with implementations. |
| https://github.com/giannifranchi/awesome-uncertainty-deeplearning | This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models. |
| https://sites.google.com/site/graphmatchingmethods/ | Efficient Methods for Graph Matching and MAP Inference |
| https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering | Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets). |
| https://github.com/jwwthu/GNN4Traffic | This is the repository for the collection of Graph Neural Network for Traffic Forecasting. |
| https://github.com/zwt233/Awesome-Auto-GNNs | A paper collection about automated graph learning |
| https://github.com/chaitjo/awesome-efficient-gnn | Efficient Graph Neural Networks - a curated list of papers and projects |
| https://github.com/Radical3-HeZhang/Awesome-Trustworthy-GNNs | Awesome Resources on Trustworthy Graph Neural Networks |
| https://github.com/EdisonLeeeee/Awesome-Masked-Autoencoders | A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.). |
| https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection | Awesome graph anomaly detection techniques built based on deep learning frameworks. |
| https://github.com/mengliu1998/awesome-expressive-gnn | A collection of papers studying/improving the expressiveness of graph neural networks (GNNs) |