Shypd.aiThe largest open index of AI toolsGraph-neural-networks is an open-source repository focused on graph neural networks (GNNs) and their applications. It provides theoretical backgrounds and implementations using TensorFlow for various GNN models.
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Graph-neural-networks is a comprehensive GitHub repository dedicated to exploring and implementing graph neural networks (GNNs). It serves as a valuable resource for understanding GNNs from theoretical foundations to practical applications using TensorFlow. The repository highlights the utility of GNNs in modeling relationships and interactions within complex systems, particularly in molecular applications, network analysis, and physics modeling. It includes various papers and tutorials covering topics such as Geometric Deep Learning, Graph Convolution Networks (GCN), Attention mechanisms in GNNs, Message Passing Neural Networks (MPNN), Graph Autoencoders, and their diverse applications.
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