Graph Neural Networks (GNNs) are a class of deep learning models designed to process and analyze graph-structured data. GNNs leverage the inherent structural information of graphs to learn powerful node and graph representations, enabling them to capture complex dependencies and propagate information effectively across the graph
Here, we will explore the capabilities of GNNs and their applications in various machine-learning tasks.
https://www.ai-contentlab.com/2023/09/an-introduction-to-graph-neural.html
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