Graph neural networks (GNNs) can be pictured as a special class of neural network models where data are structured as graphs — both training data used to train the model and real-world data used for inference — rather than fixed-size vectors or grids like image, sequences, or instances of tabular data. Graph neural networks (GNNs) can be pictured as a special class of neural network models where data are structured as graphs — both training data used to train the model and real-world data used for inference — rather than fixed-size vectors or grids like image, sequences, or instances of tabular data. 
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