GNNPapers
Graph paper collection
A curated collection of must-read papers on graph neural networks, providing a comprehensive overview of the field.
Must-read papers on graph neural networks (GNN)
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gnnpaper-list
zslucky/awesome-ai-booksRelated projects:
| Repository | Description | Stars |
|---|---|---|
 graphdeeplearning/benchmarking-gnns | A collection of datasets and tools for evaluating graph neural networks | 2,537 |
 tensorflow/gnn | Builds Graph Neural Networks on the TensorFlow platform using heterogeneous graphs and various machine learning techniques. | 1,372 |
 floodsung/deep-learning-papers-reading-roadmap | A comprehensive roadmap for learning deep learning by following key papers in the field | 38,445 |
 delta2323/gb-gnn | Analyzes and optimizes the performance of graph neural networks using gradient boosting and various aggregation models. | 13 |
 ivaniscoding/gnn-for-combinatorial-optimization | An implementation of graph neural networks for solving combinatorial optimization problems | 43 |
 google-deepmind/graph_nets | Builds graph networks in TensorFlow using a library provided by DeepMind's AI research organization. | 5,370 |
 deepgraphlearning/gmnn | A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning. | 403 |
 labmlai/annotated_deep_learning_paper_implementations | Implementations of various deep learning algorithms and techniques with accompanying documentation | 57,177 |
 dmlc/gnnlens2 | An interactive visualization tool for graph neural networks | 242 |
 dennybritz/deeplearning-papernotes | A collection of notes and summaries on various deep learning research papers, including their topics, techniques, and applications. | 4,416 |
 danielegrattarola/spektral | A Python library for building graph neural networks with Keras and TensorFlow 2. | 2,372 |
 benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 367 |
| benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 270 |
 bupt-gamma/openhgnn | An open-source toolkit for training and applying heterogeneous graph neural networks using PyTorch and the Deep Graph Library. | 879 |
| benedekrozemberczki/mixhop-and-n-gcn | A deep learning framework implementation of higher-order graph convolutional architectures and their applications | 403 |