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GNNs extend the foundational ideas of Convolutional Neural Networks (CNNs) to graph data. While CNNs capture spatial locality in grid-like data (for example, images) through convolutional kernels, ...

Using these characteristics, they simulated neural networks based on the device to classify images from the well-known MNIST database. Results revealed an online learning accuracy of 92.36%.