Understanding Graph Convolutional Networks for Node Classification
towardsdatascience.com/understanding-graph-convolutional-networks-for-node-classification-a2bfdb7aba7b
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Similar to data pre-processing for any Neural Networks operation, we need to normalize the features to prevent numerical instabilities and vanishing/exploding gradients in order for the model to converge. In GCNs, we normalize our data by calculating the Degree Matrix (D) and performing dot product operation of the inverse of D with AX
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