Graph matching and edit distance algorithms form a cornerstone of modern computational techniques used to quantify the similarity between structured data. These methods underpin a wide array of ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...
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