Shypd.aiThe largest open index of AI toolsAwesome-Graph-Neural-Networks is an academic research tool that curates paper lists for Graph Neural Networks. It provides a comprehensive collection of resources, including survey papers and research on various GNN architectures and applications.
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Awesome-Graph-Neural-Networks is a comprehensive collection of academic papers and resources focused on Graph Neural Networks (GNNs). This GitHub repository serves as a valuable reference for researchers and students, categorizing papers into various GNN types such as Recurrent, Convolutional, and Spatial-Temporal GNNs. It also covers related areas like Graph Autoencoders, Network Embedding, and Graph Generation. Additionally, the resource highlights applications of GNNs in diverse fields including Computer Vision, Natural Language Processing, Internet, Recommender Systems, Healthcare, Chemistry, and Physics. The curated lists include survey papers, foundational research, and recent advancements, making it an essential tool for staying updated on the latest developments in the field.
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