TrustAGI-Lab/Awesome-Graph-Neural-Networks

Paper Lists for Graph Neural Networks

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This is a curated collection of academic papers and resources focused on Graph Neural Networks (GNNs). It helps researchers, data scientists, and machine learning engineers stay up-to-date with the latest advancements in applying deep learning to graph-structured data. You can find comprehensive surveys, specific paper categories like recurrent or convolutional GNNs, and applications in domains like healthcare or chemistry, offering a structured entry point into complex topics.

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Use this if you are a researcher or practitioner looking for an organized overview of GNN research papers and their applications in various fields.

Not ideal if you are looking for ready-to-use code, tutorials, or software libraries to implement GNNs without diving into academic literature.

Machine Learning Research Data Science Graph Analytics Deep Learning Academic Literature
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